The Impact of Data-Driven Decision-Making, Real-Time Analytics, and Ethical Data Practices on HR Performance and Employee Satisfaction

Authors

DOI:

https://doi.org/10.56294/dm2025712

Keywords:

Data Driven Decision-Making, Real-Time Analytics, Ethical Data Practices, HR Performance, Employee Satisfaction

Abstract

Introduction: The importance of this study is to investigate decision-making by making decisions about data and real-time analytics and practicing ethical data on human resource performance and employee satisfaction.
Objective: The study was conducted at Zain Telecommunications Company Jordan through designing a questionnaire for a segmentation research in the telecommunications and exhibitions company and 220 suitable samples were removed to analyze the structural equation modeling program method SEM.
Method: The diversity of independent studies was indicated through the contracts indicating it, so multiple choices were used as evidence, workforce turnover forecasts, performance measures were available to indicate the correct decision-making to the data. Its employees were used in real time, tracking the productivity of dynamic workforce workers, and instant questionnaire mechanisms to indicate real-time analytics.
Result: Transparency in its data use policies, implementation of data privacy standards, and algorithmic fairness were used in innovative processes to indicate ethical data practices. Through the questionnaire that was distributed, these parties' studies were conducted on improving the performance of human resources and employee satisfaction.
Conclusion: His studies have concluded by integrating his three main areas of accurate decision making of his research, real-time analysis and practice of creative data and performance significantly improves the HR outcomes he chooses from employee satisfaction by choosing his specialty on data keeping pace with organizational goals by choosing his evidence.

References

1. Ahmad, H., Hanandeh, R., Alazzawi, F., Al-Daradkah, A., ElDmrat, A., Ghaith, Y., & Darawsheh, S. (2023). The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms. International Journal of Data and Network Science, 7(1), 35-40.

2. Al-Tarawneh, A., Haddada, E., Mo'd Al-Dwairi, R., Yahya Al-Freijat, S., Mansour, A., & Abdulaziz AL-Obaidly, G. (2024). The impact of strategic and innovativeness entrepreneurship and social capital on business overall performance through building a sustainable supply chain management at Jordan Private Universities.

3. Hanandeh, A., Haddad, E., Najdawi, S., & Kilani, Q. (2024). The impact of digital marketing, social media, and digital transformation on the development of digital leadership abilities and the enhancement of employee performance: A case study of the Amman Stock Exchange. International Journal of Data and Network Science, 8(3), 1915-1928.

4. Hanandeh, A., Mansour, A., Najdawi, S., Kanaan, O., Abualfalayeh, G., & Qais, K. (2024). The effect of the comprehensive quality management strategies on environmentally responsible activities and the performance of the organizations. Uncertain Supply Chain Management, 12(3), 1379-1390.

5. Mansour, A., Al-Qudah, S., Siam, Y., Hammouri, Q., & Hijazin, A. (2024). Employing E-HRM to attain contemporary organizational excellence at the Jordan social security corporation. International Journal of Data and Network Science, 8(1), 549-556.

6. Ta’Amnha, M. A., Al-Qudah, S., Asad, M., Magableh, I. K., & Riyadh, H. A. (2024). Moderating role of technological turbulence between green product innovation, green process innovation and performance of SMEs. Discover Sustainability, 5(1), 324.

7. Bousdekis, A., Lepenioti, K., Apostolou, D., & Mentzas, G. (2021). A review of data-driven decision-making methods for industry 4.0 maintenance applications. Electronics, 10(7), 828.

8. Wu, C., Wu, P., Wang, J., Jiang, R., Chen, M., & Wang, X. (2021). Critical review of data-driven decision-making in bridge operation and maintenance. Structure and infrastructure engineering, 18(1), 47-70.

9. Olaniyi, O. O., Okunleye, O. J., & Olabanji, S. O. (2023). Advancing data-driven decision-making in smart cities through big data analytics: A comprehensive review of existing literature. Current Journal of Applied Science and Technology, 42(25), 10-18.

10. Dash, B., & Ansari, M. F. (2022). Self-service analytics for data-driven decision making during COVID-19 pandemic: An organization’s best defense. Academia Letters, 2.

11. Sarkar, B. D., & Shankar, R. (2021). Understanding the barriers of port logistics for effective operation in the Industry 4.0 era: Data-driven decision making. International Journal of Information Management Data Insights, 1(2), 100031.

12. Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., ... & Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, 107547.

13. Naseer, A., Naseer, H., Ahmad, A., Maynard, S. B., & Siddiqui, A. M. (2021). Real-time analytics, incident response process agility and enterprise cybersecurity performance: A contingent resource-based analysis. International Journal of Information Management, 59, 102334.

14. Gadde, H. (2024). AI-Augmented Database Management Systems for Real-Time Data Analytics. Revista de Inteligencia Artificial en Medicina, 15(1), 616-649.

15. Valaskova, K., Machova, V., & Lewis, E. (2022). Virtual marketplace dynamics data, spatial analytics, and customer engagement tools in a real-time interoperable decentralized metaverse. Linguistic and Philosophical Investigations, 21, 105-120.

16. Mir, A. A. (2024). Optimizing mobile cloud computing architectures for real-time big data analytics in healthcare applications: Enhancing patient outcomes through scalable and efficient processing models. Integrated Journal of Science and Technology, 1(7).

17. Karunarathna, I., Gunasena, P., Hapuarachchi, T., & Gunathilake, S. (2024). Data collection fundamentals: A guide to effective research methodologies and ethical practices.

18. Chang, V. (2021). An ethical framework for big data and smart cities. Technological Forecasting and Social Change, 165, 120559.

19. Wang, C., Liu, S., Yang, H., Guo, J., Wu, Y., & Liu, J. (2023). Ethical considerations of using ChatGPT in health care. Journal of Medical Internet Research, 25, e48009.

20. Birhane, A. (2021). Algorithmic injustice: a relational ethics approach. Patterns, 2(2).

21. Ogbuke, N. J., Yusuf, Y. Y., Dharma, K., & Mercangoz, B. A. (2022). Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society. Production Planning & Control, 33(2-3), 123-137.

22. Mulang, H. (2021). The effect of competences, work motivation, learning environment on human resource performance. Golden Ratio of Human Resource Management, 1(2), 84-93.

23. Alsafadi, Y., & Altahat, S. (2021). Human resource management practices and employee performance: the role of job satisfaction. The Journal of Asian Finance, Economics and Business, 8(1), 519-529.

24. Rony, Z. T., Wijaya, I. M. S., Nababan, D., Julyanthry, J., Silalahi, M., Ganiem, L. M., ... & Saputra, N. (2024). Analyzing the Impact of Human Resources Competence and Work Motivation on Employee Performance: A Statistical Perspective. Journal of Statistics Applications & Probability, 13(2), 787-793.

25. Geethanjali, N., Ashifa, K. M., Raina, A., Patil, J., Byloppilly, R., & Rajest, S. S. (2024). Application of strategic human resource management models for organizational performance. In Data-Driven Decision Making for Long-Term Business Success (pp. 1-19). IGI Global.

26. Cao, M., Zhao, S., Chen, J., & Lv, H. (2024). Employees' HR attributions count: the effects of high-performance work systems on employees' thriving at work and emotional exhaustion. Personnel Review, 53(4), 835-856.

27. Edmans, A., Pu, D., Zhang, C., & Li, L. (2024). Employee satisfaction, labor market flexibility, and stock returns around the world. Management Science, 70(7), 4357-4380.

28. Wu, R., Zhao, X., Li, Z., & Xie, Y. (2024). The role of employee personality in employee satisfaction and turnover: insights from online employee reviews. Personnel Review.

29. Zhang, T., Zhang, J., & Tu, S. (2024). An Empirical Study on Corporate ESG Behavior and Employee Satisfaction: A Moderating Mediation Model. Behavioral Sciences, 14(4), 274.

30. Alzghoul, A., Khaddam, A. A., Alshaar, Q., & Irtaimeh, H. J. (2024). Impact of knowledge‐oriented leadership on innovative behavior, and employee satisfaction: The mediating role of knowledge‐centered culture for sustainable workplace. Business Strategy & Development, 7(1), e304.

31. Quader, M. (2024). Exploring Human Resource Management Practices and Employee Satisfaction in Bangladesh's Private Banking Sector. Journal of Policy Options, 7(1), 36-45.

32. Olawale, O., Ajayi, F. A., Udeh, C. A., & Odejide, O. A. (2024). Leveraging workforce analytics for supply chain efficiency: a review of hr data-driven practices. International Journal of Applied Research in Social Sciences, 6(4), 664-684.

33. Okatta, C. G., Ajayi, F. A., & Olawale, O. (2024). Leveraging HR analytics for strategic decision making: opportunities and challenges. International Journal of Management & Entrepreneurship Research, 6(4), 1304-1325.

34. Di Prima, C., Kotaskova, A., Yildiz, H., & Ferraris, A. (2024). How to survive social crises? An HR analytics data-driven approach to improve social sustainable operations’ effectiveness. Management Decision, 62(7), 2064-2084.

35. Alabi, K. O., Adedeji, A. A., Mahmuda, S., & Fowomo, S. (2024). Predictive Analytics in HR: Leveraging AI for Data-Driven Decision Making. International Journal of Research in Engineering, Science and Management, 7(4), 137-143.

36. Mateen, A. U., Nisar, Q. A., Jamshed, S., Rehman, S., & Ali, M. (2024). HRM Effectiveness as an Outcome of Big Data: The Role of Big Data–Driven HR Practices and Electronic HRM. Journal of the Knowledge Economy, 1-35.

37. Alabi, O. A., Ajayi, F. A., Udeh, C. A., & Efunniyi, C. P. (2024). Data-driven employee engagement: A pathway to superior customer service. World Journal of Advanced Research and Reviews, 23(3).

38. Mansour, A., Al-Qudah, S., Siam, Y., Hammouri, Q., & Hijazin, A. (2024). Employing E-HRM to attain contemporary organizational excellence at the Jordan social security corporation. International Journal of Data and Network Science, 8(1), 549-556.

39. Al-Dwairi, R., Shehabat, I., Zahrawi, A., & Hammouri, Q. (2024). Building customer trust, loyalty, and satisfaction: The power of social media in e-commerce environments. International Journal of Data and Network Science, 8(3), 1883-1894.

40. Al-Zagheer, H., AlDa'jah, A. K., Hammouri, Q., & ALShawabkeh, H. A. (2024, February). The Role of Internal Knowledge Management Capabilities with the Internet of Things. In 2024 2nd International Conference on Cyber Resilience (ICCR) (pp. 1-5). IEEE.

Downloads

Published

2025-04-05

Issue

Section

Original

How to Cite

1.
Hanandeh R, Alkhazali Z, Alhyasat KM, Mistarihi AM, Kilani QA. The Impact of Data-Driven Decision-Making, Real-Time Analytics, and Ethical Data Practices on HR Performance and Employee Satisfaction. Data and Metadata [Internet]. 2025 Apr. 5 [cited 2025 Apr. 29];4:712. Available from: https://dm.ageditor.ar/index.php/dm/article/view/712