Organizational Culture Proxies, Employee Performance, and Business Productivity Evidence from HR Analytics Data
Keywords:
Organizational culture, HR analytics, Employee performance, Business productivity, Job satisfactionAbstract
This study investigates the relationship between organizational culture proxies, employee performance and business productivity, using HR analytics data. Measurable HR indicators were used such as job satisfaction, training hours, attendance, years of experience, monthly income and hours worked per week as an indicator of the culture of an organisation, which is not an easy indicator to measure. The study adopted quantitative, cross sectional and analytical research design of which the respondents were 10,000 employees. Descriptive statistics, Pearson correlation analysis, and multiple linear regression were used to assess the impact of organizational culture-related indicators on employee performance and productivity. Of these results, the most significant were job satisfaction, projects completed, number of years of experience, monthly salary, training hours, and attendance rate. A good model's predictive ability is demonstrated by the high percentage of the variance that is accounted for in this regression model, which is 87.01%. The difference between the two was not significant, suggesting that satisfaction, development, consistency and productivity had a greater effect on performance than increased work hours. The results confirm the effectiveness of HR Analytics as a source of evidence-based information regarding organization culture and employees' performance. This research contribute to HR analytics & organizational management literature because it demonstrate the importance of capturing data about employees' regular activities to consider culture in HR related issues and increase the productivity of business.
Downloads
References
Abdullah, J. (2026). Employee Performance Metrics. https://www.kaggle.com/datasets/jamiabdullah/employee-performance-metrics
Albrecht, S., Breidahl, E., & Marty, A. (2018). Organizational resources, organizational engagement climate, and employee engagement. Career Development International, 23(1), 67–85. https://doi.org/10.1108/CDI-04-2017-0064
Bag, S., Srivastava, G., Bashir, M. M. A., Kumari, S., Giannakis, M., & Chowdhury, A. H. (2021). Journey of customers in this digital era: Understanding the role of artificial intelligence technologies in user engagement and conversion. Benchmarking: An International Journal, 29(7), 2074–2098. https://doi.org/10.1108/BIJ-07-2021-0415
Bahuguna, P. C., Srivastava, R., & Tiwari, S. (2023). Human resources analytics: Where do we go from here? Benchmarking: An International Journal, 31(2), 640–668. https://doi.org/10.1108/BIJ-06-2022-0401
Boudreau, J., & Cascio, W. (2017). Human capital analytics: Why are we not there? Journal of Organizational Effectiveness: People and Performance, 4(2), 119–126. https://doi.org/10.1108/JOEPP-03-2017-0021
Cooke, F. L., Dickmann, M., & Parry, E. (2021). IJHRM after 30 years: Taking stock in times of COVID-19 and looking towards the future of HR research. The International Journal of Human Resource Management, 32(1), 1–23. https://doi.org/10.1080/09585192.2020.1833070
E, N., Jill. (2025). Cultivating Creative Collaboration in Student Virtual Teams in Higher Education: Design and Climate: Design and Climate. IGI Global.
Espina-Romero, L., Ríos Parra, D., Noroño-Sánchez, J. G., Rojas-Cangahuala, G., Cervera Cajo, L. E., & Velásquez-Tapullima, P. A. (2024). Navigating Digital Transformation: Current Trends in Digital Competencies for Open Innovation in Organizations. Sustainability, 16(5), 2119. https://doi.org/10.3390/su16052119
Fayyad, S., Elsawy, O., Wafik, G. M., Abotaleb, S. A., Ali Abdelrahman, S. A., Abdel Moneim, A., Omran, R., Attia, S., & Mansour, M. A. (2025). Leaders’ STARA Competencies and Green Innovation: The Mediating Roles of Challenge and Hindrance Appraisals. Tourism and Hospitality, 6(4), 202. https://doi.org/10.3390/tourhosp6040202
Fernandez, V., & Gallardo-Gallardo, E. (2020). Tackling the HR digitalization challenge: Key factors and barriers to HR analytics adoption. Competitiveness Review, 31(1), 162–187. https://doi.org/10.1108/CR-12-2019-0163
Giermindl, L. M., Strich, F., Christ, O., Leicht-Deobald, U., & Redzepi, A. (2022). The dark sides of people analytics: Reviewing the perils for organisations and employees. European Journal of Information Systems, 31(3), 410–435. https://doi.org/10.1080/0960085X.2021.1927213
Jiang, K., & Messersmith, J. (2018). On the shoulders of giants: A meta-review of strategic human resource management. The International Journal of Human Resource Management, 29(1), 6–33. https://doi.org/10.1080/09585192.2017.1384930
Klimontowicz & Majewska,. (2022). The contribution of intellectual capital to banks' competitive and financial performance: The evidence from Poland. Journal of Entrepreneurship, Management and Innovation, 18(2), 105–136.
Kumar, V., Azamathulla, H. M., Sharma, K. V., Mehta, D. J., & Maharaj, K. T. (2023). The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management. Sustainability, 15(13), 10543. https://doi.org/10.3390/su151310543
Kwon, K., & Kim, T. (2020). An integrative literature review of employee engagement and innovative behavior: Revisiting the JD-R model. Human Resource Management Review, 30(2), 100704. https://doi.org/10.1016/j.hrmr.2019.100704
Levenson, A. (2018). Using workforce analytics to improve strategy execution. Human Resource Management, 57(3), 685–700. https://doi.org/10.1002/hrm.21850
Margherita, A. (2022). Human resources analytics: A systematization of research topics and directions for future research. Human Resource Management Review, 32(2), 100795. https://doi.org/10.1016/j.hrmr.2020.100795
Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. The International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
Minbaeva, D. B. (2018). Building credible human capital analytics for organizational competitive advantage. Human Resource Management, 57(3), 701–713. https://doi.org/10.1002/hrm.21848
Nisar, T. M., Prabhakar, G., & Strakova, L. (2019). Social media information benefits, knowledge management and smart organizations. Journal of Business Research, 94, 264–272. https://doi.org/10.1016/j.jbusres.2018.05.005
Otoo, F. N. K. (2019). RETRACTED: Human resource development (HRD) practices and banking industry effectiveness: The mediating role of employee competencies. European Journal of Training and Development, 43(3–4), 250–271. https://doi.org/10.1108/EJTD-07-2018-0068
Poba-Nzaou, P., Uwizeyemunugu, S., Gaha, khadija, & Laberge, M. (2020). Taxonomy of business value underlying motivations for e-HRM adoption: An empirical investigation based on HR processes. Business Process Management Journal, 26(6), 1661–1685. https://doi.org/10.1108/BPMJ-06-2018-0150
Sharma, S. K., Goyal, P., & Chanda, U. (2023). Handbook of Evidence Based Management Practices in Business. Taylor & Francis.
Sousa, M. J., & Rocha, Á. (2019). Skills for disruptive digital business. Journal of Business Research, 94, 257–263. https://doi.org/10.1016/j.jbusres.2017.12.051
Theres, C., & Strohmeier, S. (2023). Met the expectations? A meta-analysis of the performance consequences of digital HRM. The International Journal of Human Resource Management, 34(20), 3857–3892. https://doi.org/10.1080/09585192.2022.2161324
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365. https://doi.org/10.1016/j.jbusres.2016.08.009
Wang, X., Yang, J., Wang, Y., Miao, Q., Wang, F.-Y., Zhao, A., Deng, J.-L., Li, L., Na, X., & Vlacic, L. (2023). Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence. IEEE/CAA Journal of Automatica Sinica, 10(8), 1692–1703. https://doi.org/10.1109/JAS.2023.123753
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.


