Journal Screenshot

International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

Collaborative Talent Intelligence and Business Performance: A Meta-Analysis of Empirical Studies

Siti Rohaida Mohamed Zainal, Mohamed Yusoff Md Kamil

http://dx.doi.org/10.6007/IJARBSS/v16-i3/27967

Open access

Purpose – The purpose of this meta-analysis is to explore the link between collaborative talent intelligence and business performance by consolidating findings from empirical studies conducted across various industries. The review seeks to provide a clearer understanding of how organizations benefit from integrating collective workforce insights, talent data, and cross-functional collaboration into their strategic and operational practices. Design – This study adopts a meta-analysis design to systematically review, compare, and synthesize empirical research related to collaborative talent intelligence and business performance. The approach involves identifying relevant peer-reviewed studies, applying inclusion and exclusion criteria, and analysing common variables and outcome measures reported across the literature. Findings – The findings reveal that collaborative talent intelligence plays a significant role in enhancing business performance. Organizations that effectively leverage shared workforce knowledge, data-driven talent practices, and cross-departmental collaboration tend to experience improvements in innovation capability, operational efficiency, decision-making quality, and overall competitiveness. Limitation – This meta-analysis is limited by its reliance on secondary data obtained solely from published empirical studies. As a result, the review may not fully capture emerging practices, industry-specific strategies, or relevant findings contained in unpublished or practitioner-based reports. The scope is also confined to the availability and quality of existing research, which may limit the generalizability of certain conclusions across different sectors or organizational contexts. Practical Implication – The study offers practical implications for industries by emphasizing the importance of integrating collaborative talent intelligence into organizational strategies. Firms are encouraged to invest in systems that facilitate data sharing, workforce analytics, and cross-functional teamwork. By adopting these practices, industry leaders can build more agile, informed, and competitive organizations capable of sustaining strong performance in a rapidly evolving business landscape.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
Becker, B. E., & Huselid, M. A. (2014). High-performance work systems and organizational performance. Research in Personnel and Human Resources Management, 33, 53–101.
Bersin, J. (2020). Talent intelligence: Use workforce data to drive business performance. Deloitte Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10–11), 1105–1121.
Boudreau, J. W., & Cascio, W. F. (2022). Human capital analytics: Why organizations need to invest more in evidence-based talent decisions. Human Resource Management Review, 32(1), 100857.Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2005). Managing potential and realized absorptive capacity: How do organizational antecedents matter? Academy of Management Journal, 48(6), 999–1015.*
Collings, D. G., Mellahi, K., & Cascio, W. F. (2019). Global talent management and performance in multinational enterprises: A multilevel perspective. Journal of Management, 45(2), 540–566.
Huselid, M. A., & Becker, B. E. (2011). Bridging micro and macro domains: Workforce differentiation and strategic human resource management. Journal of Management, 37(2), 421–428.
Jiang, K., Lepak, D. P., Hu, J., & Baer, J. C. (2012). How does human resource management influence organizational outcomes? A meta-analytic investigation. Academy of Management Journal, 55(6), 1264–1294.
Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2005). Managing potential and realized absorptive capacity: How do organizational antecedents matter? Academy of Management Journal, 48(6), 999–1015.
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.
Peteraf, M. A., & Barney, J. B. (2003). Unraveling the resource-based tangle. Managerial and Decision Economics, 24(4), 309–323.
Richard, P. J., Devinney, T. M., Yip, G. S., & Johnson, G. (2009). Measuring organizational performance: Towards methodological best practice. Journal of Management, 35(3), 718–804.
O’Neill, T. A., & Salas, E. (2018). Creating high-performance teamwork in organizations. Human Resource Management Review, 28(4), 325–333.
Pantouvakis, A. & Vlachos, I. (2020). Talent and leadership effects on sustainable performance in the maritime industry, Transportation Research Part D: Transport and Environment, 86.
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49.*
Sirmon, D. G., Hitt, M. A., & Ireland, R. D. (2007). Managing firm resources in dynamic environments to create value: Looking inside the black box. Academy of Management Review, 32(1), 273–292.
Wright, P. M., Coff, R. W., & Moliterno, T. P. (2014). Strategic human capital: Crossing the great divide. Journal of Management, 40(2), 353–370.*
Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2015). Collective intelligence in teams and organizations. Current Directions in Psychological Science, 24(6), 420–424.*

Zainal, S. R. M., & Kamil, M. Y. M. (2026). Collaborative Talent Intelligence and Business Performance: A Meta-Analysis of Empirical Studies. International Journal of Academic Research in Business and Social Sciences, 16(3), 1136–1145.