Contribution of Human Resource Analytics Utilization to Employee Engagement in the Kenyan Banking Industry

The Kenyan banking industry is currently undergoing a rapid technological transformation, with the integration of big data and analytics emerging as key drivers of innovation and efficiency. Despite widespread recognition of the importance of employee engagement, there is a notable gap in the application of HR analytics within the Kenyan banking sector. This gap limits the precision and depth that HR analytics can offer, which could provide continuous, data- driven insights into employee engagement. This study sought to investigate the contribution of human resource analytics to employee engagement within the banking sector in Kenya. The specific objective of the study was to determine the effect of data collection methods on employee engagement within the banking sector in Kenya. The study adopted a cross-sectional research design and was anchored on Social Exchange Theory. The study targeted 1,000 employees within the banking sector in Kenya. Fisher’s two-stage formula was used to calculate a sample of 278 employees, who were then, sampled using proportionate stratified sampling. Primary data was collected using structured and semi-structured questionnaires. A pilot test was conducted with 10% of the sample, resulting in 28 employees. The study used content and construct validity, while reliability was tested using Cronbach’s Alpha, which indicated a high questionnaire reliability score of 0.747. Data was analyzed using the Statistical Package for Social Sciences (SPSS) version 23, and findings were presented in tables. The unstandardized coefficient for data collection methods (β = 0.551, p = 0.001) indicates that for each unit increase in data collection methods, employee engagement increases by approximately 0.551 units, assuming all other factors are held constant. The study recommends that banks focus on enhancing the current use of data collection methods as these have positive and significant effects on employee engagement.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-05
DOI
https://doi.org/10.5281/zenodo.14808077
Primary Topic
AI and HR Technologies
Type
article
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article

Contribution of Human Resource Analytics Utilization to Employee Engagement in the Kenyan Banking Industry

Zenodo (CERN European Organization for Nuclear Research)
AI and HR Technologies
article

Contribution of Human Resource Analytics Utilization to Employee Engagement in the Kenyan Banking Industry

article en

Abstract

The Kenyan banking industry is currently undergoing a rapid technological transformation, with the integration of big data and analytics emerging as key drivers of innovation and efficiency. Despite widespread recognition of the importance of employee engagement, there is a notable gap in the application of HR analytics within the Kenyan banking sector. This gap limits the precision and depth that HR analytics can offer, which could provide continuous, data- driven insights into employee engagement. This study sought to investigate the contribution of human resource analytics to employee engagement within the banking sector in Kenya. The specific objective of the study was to determine the effect of data collection methods on employee engagement within the banking sector in Kenya. The study adopted a cross-sectional research design and was anchored on Social Exchange Theory. The study targeted 1,000 employees within the banking sector in Kenya. Fisher’s two-stage formula was used to calculate a sample of 278 employees, who were then, sampled using proportionate stratified sampling. Primary data was collected using structured and semi-structured questionnaires. A pilot test was conducted with 10% of the sample, resulting in 28 employees. The study used content and construct validity, while reliability was tested using Cronbach’s Alpha, which indicated a high questionnaire reliability score of 0.747. Data was analyzed using the Statistical Package for Social Sciences (SPSS) version 23, and findings were presented in tables. The unstandardized coefficient for data collection methods (β = 0.551, p = 0.001) indicates that for each unit increase in data collection methods, employee engagement increases by approximately 0.551 units, assuming all other factors are held constant. The study recommends that banks focus on enhancing the current use of data collection methods as these have positive and significant effects on employee engagement.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
AI and HR Technologies
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Contribution of Human Resource Analytics Utilization to Employee Engagement in the Kenyan Banking Industry · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS