A Bibliometric Analysis of Research on Training and Labour Productivity: Trends, Themes, and Future Directions

Hang Trinh Thi Thu

Journal of Information and Knowledge Management2026https://doi.org/10.1142/s0219649225501291article
ABDC C
Weight
0.50

What the paper says

Labour productivity has been a critical area of research, particularly in addressing challenges posed by globalisation and Industry 4.0. While the importance of training in enhancing productivity is widely recognised, there is a lack of systematic research that traces evolution, trends, and thematic shifts in this field. This study addresses this gap by analysing a dataset of Scopus-indexed articles spanning from 1971 to 2024, offering an analysis of how training influences labour productivity, based on an extensive bibliometric review. Design/Methodology/Approach — From an initial pool of 1,708 documents, 552 relevant articles were selected for analysis. Through descriptive statistics and bibliometric analysis, the study reveals significant growth in research focused on the multifaceted effects of training on productivity, reflecting sustained and expanding interest in this topic. Findings — The conceptual structure of this field is visualised through scientific mapping, which identifies three primary research clusters: alignment between employer needs and higher education outcomes, core employment frameworks for productivity, and the influence of work-based learning on labour effectiveness. These clusters offer insights into the field’s foundational and emerging themes, illustrating the multidimensional role of training in meeting labour market demands. Publication activity has accelerated markedly since 2007, with 62% of all contributions appearing after 2015. The analysis of country collaboration further shows that the United States, China, and the United Kingdom are leading contributors, while the strongest international ties are observed between the United States and both China and the United Kingdom. Originality/Value — Going beyond previous studies, this research employs bibliometric methods to uncover underlying patterns and trajectories in the literature. The findings provide a roadmap for future research directions, pinpointing key areas for deeper investigation and encouraging interdisciplinary approaches to understand the enduring impact of training on labour productivity.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1142/s0219649225501291

Or copy a formatted citation

@article{hang2026,
  title        = {{A Bibliometric Analysis of Research on Training and Labour Productivity: Trends, Themes, and Future Directions}},
  author       = {Hang Trinh Thi Thu},
  journal      = {Journal of Information and Knowledge Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1142/s0219649225501291},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

A Bibliometric Analysis of Research on Training and Labour Productivity: Trends, Themes, and Future Directions

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.