MAPPING PERFORMANCE MANAGEMENT PRACTICES AND SUCCESSION PLANNING: A BIBLIOMETRIC REVIEW WITH INSIGHTS ON COGNITIVE BIAS
DOI:
https://doi.org/10.35631/IJEMP.934021Keywords:
Succession Planning, Performance Management, Cognitive BiasAbstract
This study maps the scholarly landscape of performance management practices and succession planning with particular attention to the emerging role of cognitive bias in organizational decision-making. Despite the growing importance of structured talent development and performance evaluation systems, research in this domain remains fragmented across multiple disciplines. This includes limited integration of cognitive bias perspectives that may influence managerial judgments and succession decisions. Consequently, this fragmentation poses a challenge for scholars and practitioners in understanding the field's intellectual structure and evolution. To address this gap, this study employs a bibliometric analysis approach to systematically examine global research trends. Data were retrieved from the Scopus database using advanced search strings combining two core keyword clusters: “succession planning” and “performance.” The dataset comprises 1,346 publications spanning the period from 1970 to May 2026. The analysis was conducted using Scopus Analyzer for preliminary descriptive statistics, OpenRefine for data cleaning and standardization, and VOSviewer for science mapping and visualization of co-authorship, co-citation, and keyword co-occurrence networks. The results indicate steady and accelerating growth in publications over time, particularly after 2010, reflecting increasing scholarly attention to strategic talent management and the quality of decision-making in organizations. Keyword co-occurrence analysis reveals dominant thematic clusters around leadership development, employee performance evaluation, and decision-making processes, while emerging connections highlight the integration of behavioral perspectives, including cognitive bias. Co-authorship patterns reveal strong contributions from the United States (US), the United Kingdom (UK), and selected Asian countries, indicating a geographically diverse but unevenly distributed research network. Overall, the study concludes that while performance management and succession planning are well-established fields, incorporating cognitive bias remains underexplored yet increasingly significant. Moreover, these findings provide a comprehensive intellectual structure of the field and offer directions for future research integrating behavioral science into talent management systems.
Downloads
References
Abatecola, G., Caputo, A., & Cristofaro, M. (2018). Reviewing cognitive distortions in managerial decision making. Journal of Management Development. https://doi.org/10.1108/jmd-08-2017-0263
Acciarini, C., Brunetta, F., & Boccardelli, P. (2020). Cognitive biases and decision-making strategies in times of change: a systematic literature review. Management Decision. https://doi.org/10.1108/md-07-2019-1006
Aina, R. Al, & Atan, T. (2020). The Impact of Implementing Talent Management Practices on Sustainable Organizational Performance. Sustainability. https://doi.org/10.3390/su12208372
Al-Khoury, A., Hussein, S. A., Abdulwhab, M., Aljuboori, Z. M., Haddad, H., Ali, M. A., Abed, I. A., & Flayyih, H. H. (2022). Intellectual Capital History and Trends: A Bibliometric Analysis Using Scopus Database. Sustainability (Switzerland), 14(18). https://doi.org/10.3390/su141811615
Alves, J. L., Borges, I. B., & De Nadae, J. (2021). Sustainability in complex projects of civil construction: Bibliometric and bibliographic review. Gestao e Producao, 28(4). https://doi.org/10.1590/1806-9649-2020v28e5389
Andersen, S., & Hjortskov, M. (2016). Cognitive Biases in Performance Evaluations. Journal of Public Administration Research and Theory, 26, 647–662. https://doi.org/10.1093/jopart/muv036
Appio, F. P., Cesaroni, F., & Di Minin, A. (2014). Visualizing the structure and bridges of the intellectual property management and strategy literature: a document co-citation analysis. Scientometrics, 101(1), 623–661. https://doi.org/10.1007/s11192-014-1329-0
Assyakur, D. S., & Rosa, E. M. (2022). Spiritual Leadership in Healthcare: A Bibliometric Analysis. Jurnal Aisyah : Jurnal Ilmu Kesehatan, 7(2). https://doi.org/10.30604/jika.v7i2.914
Berthet, V. (2020). The Impact of Cognitive Biases on Professionals’ Decision-Making: A Review of Four Occupational Areas. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.802439
Carter, L., & Liu, D. (2025). How was my performance? Exploring the role of anchoring bias in AI-assisted decision making. Int. J. Inf. Manag., 82, 102875. https://doi.org/10.1016/j.ijinfomgt.2025.102875
Collings, D. G., & Mellahi, K. (2009). Strategic talent management: A review and research agenda. Human Resource Management Review, 19(4), 304–313. https://doi.org/10.1016/j.hrmr.2009.04.001
di Stefano, G., Peteraf, M., & Veronay, G. (2010). Dynamic capabilities deconstructed: A bibliographic investigation into the origins, development, and future directions of the research domain. Industrial and Corporate Change, 19(4), 1187–1204. https://doi.org/10.1093/icc/dtq027
Edvinsson, L. (1997). Developing intellectual capital at Skandia. Long Range Planning, 30(3), 366-373+320. https://doi.org/10.1016/s0024-6301(97)00016-2
Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). Green supply chain management: A review and bibliometric analysis. In International Journal of Production Economics (Vol. 162, pp. 101–114). https://doi.org/10.1016/j.ijpe.2015.01.003
Fasolo, B., Heard, C., & Scopelliti, I. (2024). Mitigating Cognitive Bias to Improve Organizational Decisions: An Integrative Review, Framework, and Research Agenda. Journal of Management, 51, 2182–2211. https://doi.org/10.1177/01492063241287188
Feldman, J. (1981). Beyond Attribution Theory: Cognitive Processes in Performance Appraisal. Journal of Applied Psychology, 66, 127–148. https://doi.org/10.1037/0021-9010.66.2.127
Gardner, W. L., Avolio, B. J., Luthans, F., May, D. R., & Walumbwa, F. (2005). “Can you see the real me?” A self-based model of authentic leader and follower development. Leadership Quarterly, 16(3), 343–372. https://doi.org/10.1016/j.leaqua.2005.03.003
Groves, K. (2017). Examining the impact of succession management practices on organizational performance: A national study of U.S. hospitals. Health Care Management Review. https://doi.org/10.1097/hmr.0000000000000176
Gruman, J. A., & Saks, A. M. (2011). Performance management and employee engagement. Human Resource Management Review, 21(2), 123–136. https://doi.org/10.1016/j.hrmr.2010.09.004
Gu, D., Li, T., Wang, X., Yang, X., & Yu, Z. (2019). Visualizing the intellectual structure and evolution of electronic health and telemedicine research. International Journal of Medical Informatics, 130. https://doi.org/10.1016/j.ijmedinf.2019.08.007
Hristov, I., Camilli, R., & Mechelli, A. (2022). Cognitive biases in implementing a performance management system: behavioral strategy for supporting managers’ decision-making processes. Management Research Review. https://doi.org/10.1108/mrr-11-2021-0777
Khiste, G. P., & Paithankar, R. R. (2017). Analysis of Bibliometric term in Scopus. International Research Journal, 01(32), 78–83.
Kumari, A., & Agnihotri, Dr. A. (2024). Effect of Succession Planning in Banking Industry. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. https://doi.org/10.55041/ijsrem36615
Liden, R. C., Wayne, S. J., Zhao, H., & Henderson, D. (2008). Servant leadership: Development of a multidimensional measure and multi-level assessment. Leadership Quarterly, 19(2), 161–177. https://doi.org/10.1016/j.leaqua.2008.01.006
Lord, R. G., & Hall, R. J. (2005). Identity, deep structure and the development of leadership skill. Leadership Quarterly, 16(4), 591–615. https://doi.org/10.1016/j.leaqua.2005.06.003
M, Nandini., & Archana. (2024). Impact of Succession Planning on Organizational Performance. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-22346
Marler, J. H., & Boudreau, J. W. (2017). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
Nduati, M. M. (2022). EMPLOYEE PERFORMANCE MANAGEMENT PRACTICES AND ORGANIZATIONAL EFFECTIVENESS. https://consensus.app/papers/employee-performance-management-practices-and-nduati/1f0fc981357b5127ba298b2849bd0d8f/
Ng, K.-Y., Van Dyne, L., & Ang, S. (2009). From experience to experiential learning: Cultural intelligence as a learning capability for global leader development. Academy of Management Learning and Education, 8(4), 511–526. https://doi.org/10.5465/amle.8.4.zqr511
Padma Dr. Satuluri, M. M. (2024). Holistic approach of Talent Management for a successful Succession Planning. Journal of Informatics Education and Research. https://doi.org/10.52783/jier.v4i1.638
Purnamawati, R. F. (2024). The Role of Cognitive Bias in Principal Decision Making: A Narrative Analysis of the Literature. PPSDP International Journal of Education. https://doi.org/10.59175/pijed.v3i2.310
Qazi, S., Shrivastava, P., Upadhyaya, A., Shukla, A., Bharadwaj, V., Pawan, & Paras, K. (2025). The Role of Succession Planning in Private Organisations. Journal of Information Systems Engineering and Management. https://doi.org/10.52783/jisem.v10i49s.10004
Rau, D., & Bromiley, P. (2025). A REVIEW OF COGNITIVE BIASES IN STRATEGIC DECISION MAKING. Long Range Planning. https://doi.org/10.1016/j.lrp.2025.102529
Schroth, H. (2019). Are you ready for gen Z in the workplace? California Management Review, 61(3), 5–18. https://doi.org/10.1177/0008125619841006
Shet, Sateesh., Patil, S., & Chandawarkar, M. (2019). Competency based superior performance and organizational effectiveness. International Journal of Productivity and Performance Management. https://doi.org/10.1108/ijppm-03-2018-0128
Tarimo, E., Mzava, H. Y., & Kyando, E. (2024). Effect of Succession Planning Practices on NGOS Performance in Tanzania. European Journal of Management Issues. https://doi.org/10.15421/192414
Van Eck, N. J., & Waltman, L. (2007). Bibliometric mapping of the computational intelligence field. International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems, 15(5), 625–645. https://doi.org/10.1142/S0218488507004911
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070. https://doi.org/10.1007/s11192-017-2300-7
Verbeek, A., Debackere, K., Luwel, M., & Zimmermann, E. (2002). Measuring progress and evolution in science and technology - I: The multiple uses of bibliometric indicators. International Journal of Management Reviews, 4(2), 179–211. https://doi.org/10.1111/1468-2370.00083
Walumbwa, F. O., Avolio, B. J., Gardner, W. L., Wernsing, T. S., & Peterson, S. J. (2008). Authentic leadership: Development and validation of a theory-based measure. Journal of Management, 34(1), 89–126. https://doi.org/10.1177/0149206307308913
Wu, Y. C. J., & Wu, T. (2017). A decade of entrepreneurship education in the Asia Pacific for future directions in theory and practice. In Management Decision (Vol. 55, Number 7, pp. 1333–1350). https://doi.org/10.1108/MD-05-2017-0518
