Decoding Employee Loyalty: Unravelling The Impact of Human Resource Analytics in Uganda's Commercial Banking Sector
DOI:
https://doi.org/10.54099/aijb.v3i2.991Keywords:
Human Resource Analytics, Staff Retention, Commercial Bank, UgandaAbstract
The study examined the effect of human resource analytics on staff retention in commercial banks in Uganda, a case of Finance Trust Bank, main branch. The study objectives included; (i) to evaluate the effect of HR data mining analytics on staff retention in Finance Trust Bank; (ii)to determine the effect of HR data interpretation analytics on staff retention in Finance Trust Bank and (iii) to examine the effect of HR performance management analytics on staff retention in Finance Trust Bank. The study design was a cross sectional design and the approaches used were both qualitative and quantitative. The study population was 65 people, a census was adopted; 53 respondents responded, thus a response rate of 82%. Questionnaires were the main tools used in data collection. The findings indicated that performance management analytics is the greatest contributor to employee retention in Finance Trust Bank (β = 0.566; p value = 0.001), data mining analytics is the second contributor to employee retention (β= 0.373; p value= 0.006), and data interpretation analytics is the least contributor to employee retention (β = 0.211; p value= 0.039). The study concluded that data mining analytics, data interpretation analytics and performance management analytics are all strong, positive and significant predictors of employee retention at the bank (R2 =.647; p value = 0.000). Conclusion were drawn and recommendations given.
References
Al-sharafi, H., & Rajiani, I. (2013). Promoting organizational citizenship behavior among employees-the role of leadership practices. International Journal of Business and Management, 8(6), 47.
Al-sharafi, H., Hassan, M. E. M., & Alam, S. S. (2018). The Effect of Training and Career Development on Employees Retention: A Study on the Telecommunication Organizations in Yemen. The Journal of Social Sciences Research, 420-430.
Al-Sharifi, H. & Rajiani, L. (2013). Leadership practices and talent turnover, study on
Antwi, S., & Binfor, F. (2013). The effect of corporate governance on strategic change in financial institutions: Evidence from Ghana. International Journal of Academic Research in Business and Social Sciences, 3(3), 159.
Armstrong, M. (2004). Human Resource Management Theory and Practice. London: Bath Press Ltd.
Beatty, R. (2015). Relationship between Human Resource Analytics and employee’s motivation in the nonprofit organizations of Pakistan. Business Intelligent Journal, 4(2): 327-334.
Bø, E., Hovi, I. B., & Pinchasik, D. R. (2022). COVID-19 disruptions and Norwegian food and pharmaceutical supply chains: Insights into supply chain risk management, resilience, and reliability. Sustainable Futures, 100102.
Charles, E. (2014). Employee Benefits, retention and Continuance Commitment in the Nigerian Manufacturing Industry. Journal of Business and Management, 16(2): 69-74.
Davenportet, E. (2010). Radical HRM innovation and competitive advantage: the money ball story, Human Resource Management, 45(1), 111-126
Dulebohn, F. (2015). The Rise of HR: Wisdom from 73 Thought Leaders, HR Certification Institute, Alexandria, VA, pp. 301-315.
Dysvik, A., & Kuvaas, B. (2013). Perceived job autonomy and turnover intention: The moderating role of perceived supervisor support. European Journal of Work and Organizational Psychology, 22(5), 563-573.
Echol, C. (2012). Celebrating 50 years: looking back and looking forward: 50 years of human resource management, Human Resource Management, 50(3), 309-312
Fitz-enz, C. &Matox, F. (2015). Human resource information systems: operational issues and strategic considerations in a global environment, International Journal of Human Resource Management, 7 (1), 245-269
Haile, G. A. (2015). Workplace Job Satisfaction in B ritain: Evidence from Linked Employer–Employee Data. Labour, 29(3), 225-242.
Heron, A. (2014). New HR Analytics: Predicting the Economic Value of Your Company’s Human Capital Investments, AMACOM, New York, NY.
Hughes, J. C., & Rog, E. (2008). Talent management: A strategy for improving employee recruitment, retention and engagement within hospitality organizations. International Journal of Contemporary Hospitality Management,20(7),743-757.
Islami, X., Mulolli, E., & Mustafa, N. (2018). Using Management by Objectives as a performance appraisal tool for employee satisfaction. Future Business Journal, 4(1), 94-108.
Isson, J. P., & Harriott, J. S. (2016). People analytics in the era of big data: Changing the way you attract, acquire, develop, and retain talent. John Wiley & Sons.
Joih, F. (2014). Using the Delphi technique to predict future staff retention, Marketing Intelligence & Planning, 12 (7), 18-29
Kashive, N., & Khanna, V. T. (2022). Emerging HR analytics role in a crisis: an analysis of LinkedIn data. Competitiveness Review: An International Business Journal, (ahead-of-print).
Khan, S. A., & Tang, J. (2016). The paradox of human resource analytics: being mindful of employees. Journal of General Management, 42(2), 57-66.
Koay, K. Y., & Soh, P. C. H. (2018, August). Does cyberloafing really harm employees’ work performance?: an overview. In International Conference on Management Science and Engineering Management (pp. 901-912). Springer, Cham.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610.
Kukano, E. (2014). Human resource information systems”, Proceedings of the 3rd International Workshop on Human Resource Information Systems – HRIS 2009, INSTICC Press.
Laroche, P. (2017). Union membership and job satisfaction: Initial evidence from French linked employer–employee data. Human Resource Management Journal, 27(4), 648-668.
Linoff, G. S., & Berry, M. J. (2011). Data mining techniques: for marketing, sales, and customer relationship management. John Wiley & Sons.
Mikalef, P., Pappas, I., Krogstie, J., & Pavlou, P. (2019). Big data and business analytics: A research agenda for realizing business value.
Mohammed, D., & Quddus, A. (2019). HR analytics: a modern tool in HR for predictive decision making. Journal of Management, 6(3).
Müceldili, B., Turan, H., & Erdil, O. (2013). The influence of authentic leadership on creativity and innovativeness. Procedia-Social and Behavioral Sciences, 99, 673-681.
Mugenda, O. M., & Mugenda, A. G. (2003). Research methods: Quantitative and. Qualitative. Approaches. Nairobi; African Centre for Technology Studies.
Nathan, B. (2014). People are the real numbers: HR analytics has come of age, a report by KPMG International Cooperative
Nohria, A., Hasselblad, V., Stebbins, A., Pauly, D. F., Fonarow, G. C., Shah, M., ... & Hill, J. A. (2008). Cardiorenal interactions: insights from the ESCAPE trial. Journal of the American College of Cardiology, 51(13), 1268-1274.
Noreen, V. (2017). HR metrics and analytics uses and impacts on staff retention, working paper, – CEO Publication, Los Angeles, CA, available at: http://classic.marshall.usc.edu/assets/048/ 9984.pdf (accessed December 7, 2019).
Osibanjo, O. A., Adeniji, A. A., Falola, H. O., & Heirsmac, P. T. (2014). Compensation packages: a strategic tool for employees’ performance and retention. Leonardo Journal of Sciences, 25(1), 65-84.
Rasmussen, T., & Ulrich, D. (2015). Learning from practice: how HR analytics avoids being a management fad. Organizational Dynamics, 44(3), 236-242.
Schiemann, W. A. (2014). From talent management to talent optimization. Journal of World Business, 49(2), 281-288.
Schwabenland, K. & Wei, P. (2015). An evidence-based review of e-HRM and strategic human resource management, Human Resource Management Review, Vol. 23 No. 1, pp. 18-36.
Shah, N., Irani, Z., & Sharif, A. M. (2017). Big data in an HR context: Exploring organizational change readiness, employee attitudes and behaviors. Journal of Business Research, 70, 366-378.
Sharma, A., & Sharma, T. (2017). HR analytics and performance appraisal system: A conceptual framework for employee performance improvement. Management Research Review, 40(6), 684-697.
Tanton, W. (2016). A Delphi study of knowledge management systems: scope and requirements, Information & Management, 44(6), 583-597
Tanwar, K., & Prasad, A. (2016). Exploring the relationship between employer branding and employee retention. Global business review, 17(3_suppl), 186S-206S.
Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Sage.
Thunnissen, R. (2017). Applying Advanced Analytics to HR Management Decisions, Pearson Education, Inc., Journal of Human Resource Management, 6(8), 13-17.
Tiwari, I. (2015). An analysis of the factors affecting employee retention and turnover in the Irish hospitality industry (Doctoral dissertation, Dublin, National College of Ireland).
van Vulpen, E. (2016, June 16). Predictive Analytics in Human Resources: Tutorial and 7 case studies. AIHR; AIHR | Academy to Innovate HR. https://www.aihr.com/blog/predictive-analytics-human-resources/
Verine, A. 2015.Individual privacy and computer-based human resource information systems, Journal of Business Ethics, 8 (1) 569-576.
Yemeni organisations. Business and Management Research, 2(3), 60-67
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Asean International Journal of Business
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
