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Authors
1 Ikongha Isong Owor; 2 Abraham Olatubosun; 3 Nkem Jennifer Majeed-Raji; 4 Omagbedhe Goddy Aworawo; 5 Oseni Salami
1, 4 & 5Department of Business Administration, Faculty of Management Sciences, National Open University of Nigeria, Abuja, Nigeria
2Department of Business Administration, Faculty of Management Sciences, Nasarawa State University Keffi, Nigeria.
3Dept of Public Administration, Faculty of Management Sciences, National open University of Nigeria, Abuja, Nigeria.
Abstract
This study investigated the relationship between organisational ambidexterity and sustainable performance, specifically evaluating the mediating mechanism of strategic agility. Anchored in dynamic capabilities theory and the resource-based view, the inquiry addressed ongoing questions about why structural investments in dual operational strategies do not uniformly enhance triple-bottom-line outcomes in volatile financial markets. The study used a quantitative survey methodology and collected empirical data from 202 managerial and professional staff at Access Bank in Nigeria. Hypothesized paths and structural relationships were evaluated through partial least squares structural equation modeling. The empirical assessment revealed that organisational ambidexterity exerted a meaningful, positive direct influence on both sustainable performance and strategic agility. Strategic agility similarly exercised a robust, positive direct effect on sustainable performance metrics. Beyond these direct linkages, the mediation analysis showed that strategic agility served as a complementary partial mediator, linking ambidextrous operational structures to firm-level economic, social, and environmental outcomes. Overall, the findings confirmed that balanced structural frameworks alone remained insufficient to drive corporate sustainability without environmental sensitivity, unified leadership, and rapid resource reallocation. The study therefore underscored that banking executives seeking sustained competitive advantage must synchronize dual-operational designs with agile management practices that systematically cultivate structural flexibility.
Keywords: Dynamic Capabilities Theory, Strategic Agility, Sustainable Performance, Organisational Ambidexterity, Partial Least Squares Structural Equation Modeling.
References
Access Bank. (2026). Sustainable banking: Our approach and policies. https://www.accessbankplc.com/sustainable-banking/our-approach
Ayoub, H. S., & Salloum, J. C. (2026). Reconfiguring strategic capabilities in the digital era: The roles of AI-enabled dynamic capability, data-driven culture, and organizational learning. Sustainability, 18(3), 1157. https://doi.org/10.3390/su18031157
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Bui, T.-D., Tsai, F. M., Tseng, M.-L., Tan, R. R., Yu, K. D. S., & Lim, M. K. (2021). Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis. Sustainable Production and Consumption, 26, 373–410. https://doi.org/10.1016/j.spc.2020.09.017
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates.
Demirci, U., Makridis, C. A., Papanikolaou, N., & Tüysüz, F. (2025). Online labor markets: Declining demand for writing and design, rising complexity. Journal of Labor Economics. https://doi.org/10.1086/jle.2025.demirci
Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2–3), 370–382. https://doi.org/10.1016/j.lrp.2009.07.006
Gao, Y., Liu, S., & Yang, L. (2025). Artificial intelligence and innovation capability: A dynamic capabilities perspective. International Review of Economics & Finance, 98, 103923. https://doi.org/10.1016/j.iref.2025.103923
Guarín-García, M., & Chams-Anturi, O. (2026). Organizational ambidexterity in emerging markets: A bibliometric analysis. Journal of Innovation Management, 13(4), 50–75. https://doi.org/10.24840/2183-0606_013.004_0003
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.
Junni, P., Sarala, R. M., Tarba, S. Y., & Weber, Y. (2020). The role of strategic agility in organizational ambidexterity. British Journal of Management, 31(3), 541–558. https://doi.org/10.1111/1467-8551.12392
Kafetzopoulos, P., Psomas, E., & Katou, A. A. (2023). Promoting strategic flexibility and business performance through organizational ambidexterity. Sustainability, 15(17), 12997. https://doi.org/10.3390/su151712997
Li, K., Cai, Y., Pei, Y., & Yuan, C. (2025). The impact of artificial intelligence adoption on firms’ innovation performance in the digital era: Based on dynamic capabilities theory. International Theory and Practice in Humanities and Social Sciences, 2(3), 228–237. https://doi.org/10.70693/itphss.v2i3.343
March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. https://doi.org/10.1287/orsc.2.1.71
Mikalef, P., Pateli, A., Batenburg, R., & van de Wetering, R. (2023). Purchasing data analytics capability: Implications from the resource-based view and absorptive capacity theory. Information & Management, 60(2), 103742. https://doi.org/10.1016/j.im.2022.103742
Nugroho, W. (2026). Strategic agility as a dynamic capability for corporate sustainability. Proceedings of the International Conference on Management and Information Technology, 126022014.
O’Reilly, C. A., & Tushman, M. L. (2013). Organizational ambidexterity in action: How managers explore and exploit. California Management Review, 55(4), 5–25. https://doi.org/10.1525/cmr.2013.55.4.5
Rammer, C., Fernández, G. P., Czarnitzki, D., Doherr, T., Hud, M., Köhler, C., & Schwiebacher, F. (2022). Artificial intelligence and industrial innovation: Evidence from German firm-level data (ZEW Discussion Paper No. 22-028). ZEW – Leibniz Centre for European Economic Research. https://doi.org/10.2139/ssrn.4174312
Samimi Dehkordi, S., Pourkiani, M., & Fathi, A. (2025). The impact of AI usage on innovation behavior at work: The moderated mediating effects of openness and job complexity. Frontiers in Psychology, 15, 1544103. https://doi.org/10.3389/fpsyg.2025.1544103
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2022). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 587–632). Springer. https://doi.org/10.1007/978-3-319-05542-8_15-2
Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill-building approach (7th ed.). Wiley.
Sowa, K., Przegalinska, A., & Ciechanowski, L. (2021). Cobots in knowledge work: Human-AI collaboration in managerial professions. Journal of Business Research, 131, 587–597. https://doi.org/10.1016/j.jbusres.2020.10.035
Tallon, P. P., & Pinsonneault, A. (2023). Competing on agility: Information technology and the dynamics of strategic responsiveness. Journal of Management Information Systems, 40(2), 412–439. https://doi.org/10.1080/07421222.2023.2196884
Teece, D. J. (2018). Dynamic capabilities as (workable) management systems theory. Journal of Management & Organization, 24(3), 359–368. https://doi.org/10.1017/jmo.2017.159
Xu, X., Liu, W., & Gursoy, D. (2025). Human-AI collaboration in service delivery: A systematic review and research agenda. International Journal of Contemporary Hospitality Management, 37(2), 512–534. https://doi.org/10.1108/IJCHM-2025.xu