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The Impact of Human Resource Management Practices on Farms Development and Succession Planning – a PLS-SEM Approach

Marius Ogrezeanu et al.

Economics and Applied Informatics2025https://doi.org/10.35219/eai15840409481article
ABDC C
Weight
0.50

What the paper says

This study examines the impact of Human Resource Management (HRM) practices on farm development, employer branding, and succession planning in the agricultural sector.Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the research analyzes data from farm owners across different geographical regions to explore the relationships between HR strategies, workforce challenges, and long-term business sustainability.The findings highlight that effective recruitment, selection, and employee retention strategies significantly influence farm expansion, workforce motivation, and investment in training programs.Additionally, the study confirms a strong correlation between farm development intentions and succession planning, demonstrating that farmers with a strategic growth mindset are more likely to engage in structured succession planning.Employer branding and retention policies are key determinants of workforce stability, reinforcing that farms perceived as attractive employers are better positioned to retain skilled employees and ensure business continuity.While HRM challenges have a moderate but statistically insignificant negative impact on employer branding, farmers often mitigate these issues through adaptive strategies such as seasonal workforce collaborations.The study's practical implications suggest that policymakers and agricultural stakeholders should develop targeted HR support programs to enhance employee retention and succession planning.

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https://doi.org/https://doi.org/10.35219/eai15840409481

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@article{marius2025,
  title        = {{The Impact of Human Resource Management Practices on Farms Development and Succession Planning – a PLS-SEM Approach}},
  author       = {Marius Ogrezeanu et al.},
  journal      = {Economics and Applied Informatics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.35219/eai15840409481},
}

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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.