Moderating role of technology acceptance on the relationship between digital HRM practices and organizational performance: Evidence from organizations in Dar es Salaam and Dodoma cities, Tanzania

Mashala L. Yusuph; Lazaro A. Kisumbe; John W. Kasubi

doi:10.51867/AQSSR.3.2.4

Auteurs-es

Mashala L. Yusuph The Local Government Training Institute, P. O. Box 1125, Dodoma, Tanzania Auteur-e https://orcid.org/0000-0003-2221-845X
Lazaro A. Kisumbe The Local Government Training Institute, P. O. Box 1125, Dodoma, Tanzania Auteur-e https://orcid.org/0009-0002-5064-1650
John W. Kasubi The Local Government Training Institute, P. O. Box 1125, Dodoma, Tanzania Auteur-e

DOI :

https://doi.org/10.51867/AQSSR.3.2.4

Mots-clés :

Digital HRM, e-HRM, Organizational Performance, Technology Acceptance, Tanzania

Résumé

Digital transformation has altered human resource management (HRM) worldwide, but its performance outcomes in emerging economies are not yet well researched, especially the conditional role of user acceptance. This paper investigates the moderating role of technology acceptance on the relationship between digital HRM practices and organizational performance in Tanzania. The research is based on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Resource-Based View (RBV). The hypotheses are that digital HRM practices positively influence performance, technology acceptance directly influences the main effect, and acceptance enhances it. The survey was a quantitative cross-sectional study of 304 ICT and HR professionals and managers in all public and private organizations in Dar es Salaam and Dodoma, selected using purposive sampling. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 4. Findings show that digital HRM practices contribute to organizational performance in a significant and positive manner, technology acceptance has a direct and positive effect, and acceptance moderates the relationship positively. The model is a strong predictive model that explains 58% of the variance in performance. Theoretically, this research takes a step toward the integration of personal acceptance variables and organizational resource perspectives in an African context. In practice, user-focused training, user-friendly interfaces, and change management should be prioritized in organizations to enhance the benefits of digital HRM and achieve long-term competitive advantage. To facilitate the introduction of inclusive and sustainable HRM change across Tanzania, policymakers must implement acceptance-based interventions within national strategies for a digital economy, public sector reforms, and Vision 2050 initiatives.

Références

Akankunda, B., Nkundabanyanga, S. K., Kaawaase, T. K., Adaramola, M. S., Nkurunziza, G., & Tumwine, S. (2024). The mediating effect of management control systems on human capital and sustainable performance among Ugandan power companies. Cogent Business & Management, 11(1). https://doi.org/10.1080/23311975.2024.2324369 DOI: https://doi.org/10.1080/23311975.2024.2324369

Alomari, A. M. (2023). Exploring the impact of e-HRM on organizational performance: A mediated model. International Journal of Data and Network Science, 7, 1913-1920. https://doi.org/10.5267/j.ijdns.2023.7.002 DOI: https://doi.org/10.5267/j.ijdns.2023.7.002

Amoako, R., Jiang, Y., Adu-Yeboah, S. S., Frempong, M. F., & Tetteh, S. (2023). Factors influencing electronic human resource management implementation in public organisations in an emerging economy: An empirical study. South African Journal of Business Management, 54(1), 1-12. https://doi.org/10.4102/sajbm.v54i1.2937 DOI: https://doi.org/10.4102/sajbm.v54i1.2937

Asamoah-Appiah, W., Kesari, S., & Bartrop-Sackey, M. (2024). The impact of electronic human resource management (e-HRM) on non-financial organisational performance: Perspective of multinational companies in Ghana. Global Journal of Human Resource Management, 12(7), 67-99. https://doi.org/10.37745/gjhrm.2013/vol12n76799 DOI: https://doi.org/10.37745/gjhrm.2013/vol12n76799

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.

https://doi.org/10.1177/014920639101700108 DOI: https://doi.org/10.1177/014920639101700108

Bendera, E. D., Chong, Y., & Ng, L. P. (2025). How human resource practices, organisational support and trustworthiness shape job satisfaction. SA Journal of Human Resource Management, 23, 1-14. https://doi.org/10.4102/sajhrm.v23i0.29188 DOI: https://doi.org/10.4102/sajhrm.v23i0.2918

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008 DOI: https://doi.org/10.2307/249008

Faustine, P., & Rachmawati, R. (2024). AI adoption determinants and its impacts on HRM effectiveness within MES in Tanzania. Open Journal of Business and Management, 12, 2532-2552. https://doi.org/10.4236/ojbm.2024.124131 DOI: https://doi.org/10.4236/ojbm.2024.124131

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage. https://doi.org/10.1007/978-3-030-80519-7 DOI: https://doi.org/10.1007/978-3-030-80519-7

Mbamba, U. O. L., & Sanga, J. J. (2024). Influence of electronic human resource management on supporting staff job performance among selected Tanzanian public universities. University of Dar es Salaam Library Journal, 19(1), 156-172. https://doi.org/10.4314/udslj.v19i1.11 DOI: https://doi.org/10.4314/udslj.v19i1.11

Menant, L., Gilibert, D., & Sauvezon, C. (2021). The application of acceptance models to human resource information systems: A literature review. Frontiers in Psychology, 12, 659421. https://doi.org/10.3389/fpsyg.2021.659421 DOI: https://doi.org/10.3389/fpsyg.2021.659421

Priyashantha, K. G., & Chandradasa, A. H. I. (2023). Electronic human resource management (e-HRM) adoption: A systematic literature review. Sri Lanka Journal of Social Sciences, 46(1), 19-37. https://doi.org/10.4038/sljss.v46i1.8573 DOI: https://doi.org/10.4038/sljss.v46i1.8573

Ruiz, L., Benítez, J., Castillo, A., & Braojos, J. (2024). Digital human resource strategy: Conceptualization, theoretical development, and an empirical examination of its impact on firm performance. Information & Management, 61(4), 103966. https://doi.org/10.1016/j.im.2024.103966 DOI: https://doi.org/10.1016/j.im.2024.103966

Seni, A. S., Chachage, B., & Kapaya, S. (2025). Influence of electronic human resource management on supporting staff job performance among selected Tanzanian public universities. The Pan-African Journal of Business Management, 9(2), 46-59. https://doi.org/10.61538/pajbm.v9i2.1890 DOI: https://doi.org/10.61538/pajbm.v9i2.1890

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 DOI: https://doi.org/10.1080/09585192.2022.2161324

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://www.jstor.org/stable/30036540 DOI: https://doi.org/10.2307/30036540

Zhou, Y., Cheng, Y., Zou, Y., & Liu, G. (2022). e-HRM: A meta-analysis of the antecedents, consequences, and cross-national moderators. Human Resource Management Review, 32(4), 1-21. https://doi.org/10.1016/j.hrmr.2021.100862 DOI: https://doi.org/10.1016/j.hrmr.2021.100862