Talent Identification and Staff Performance of Public Hospitals in Busia County

Purpose: To establish the effect of talent identification on staff performance of public hospitals in Busia County Design/Methodology/Approach: An explanatory research design was employed, targeting 255 employees across 11 public hospitals in Busia County, with data collected through structured questionnaires. A pilot study involving 25 respondents from Matungu Hospital in Kakamega County was conducted to pretest the research instrument. Piloting would help identify ambiguities and ensure clarity, allowing for necessary adjustments before the main data collection. To ensure validity, the study used expert review to assess content and construct validity, while reliability was tested using Cronbach’s alpha to determine the internal consistency of the research instrument, with a threshold of 0.7 considered acceptable. Data was analyzed using both descriptive statistics (frequencies, means, standard deviations) and inferential statistics (regression analysis, correlation, and moderation analysis) via SPSS software Findings: The study found that talent identification had strong relationships with staff performance in Public Hospitals in Busia County Kenya. Talent identification had a statistically significant contribution to the staff performance of Public Hospitals in Busia County (b=0.516 t=26.110 p=0.000<0.05). Implications/Originality/Value: The study recommends that Public Hospitals should ensure that they prioritize the key factors that impact their staff performance.

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Publication Details

Journal
Journal of Business and Social Review in Emerging Economies
Published
2025-09-30
DOI
https://doi.org/10.26710/jbsee.v11i3.3473
Primary Topic
Human Resource and Talent Management
Type
article
Field-Weighted Citation Impact
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article

Talent Identification and Staff Performance of Public Hospitals in Busia County

Olivier Léonard, Eglay Tsuma, Rosemary Nanyama Mumaraki
Journal of Business and Social Review in Emerging Economies
Human Resource and Talent Management
article

Talent Identification and Staff Performance of Public Hospitals in Busia County

Olivier Léonard, Eglay Tsuma, Rosemary Nanyama Mumaraki
article en

Abstract

Purpose: To establish the effect of talent identification on staff performance of public hospitals in Busia County Design/Methodology/Approach: An explanatory research design was employed, targeting 255 employees across 11 public hospitals in Busia County, with data collected through structured questionnaires. A pilot study involving 25 respondents from Matungu Hospital in Kakamega County was conducted to pretest the research instrument. Piloting would help identify ambiguities and ensure clarity, allowing for necessary adjustments before the main data collection. To ensure validity, the study used expert review to assess content and construct validity, while reliability was tested using Cronbach’s alpha to determine the internal consistency of the research instrument, with a threshold of 0.7 considered acceptable. Data was analyzed using both descriptive statistics (frequencies, means, standard deviations) and inferential statistics (regression analysis, correlation, and moderation analysis) via SPSS software Findings: The study found that talent identification had strong relationships with staff performance in Public Hospitals in Busia County Kenya. Talent identification had a statistically significant contribution to the staff performance of Public Hospitals in Busia County (b=0.516 t=26.110 p=0.000<0.05). Implications/Originality/Value: The study recommends that Public Hospitals should ensure that they prioritize the key factors that impact their staff performance.

Journal of Business and Social Review in Emerging EconomiesVol. 11(3)
Masinde Muliro University of Science and Technology (KE)
Openalex Percentile: Top 66%
Human Resource and Talent Management
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Talent Identification and Staff Performance of Public Hospitals in Busia County — Olivier Léonard, Eglay Tsuma, et al. · Journal of Business and Social Review in Emerging Economies (2025) | TGRS Research Map | TGRS