Business Analytics Capability and Competitive Advantage: The Mediating Role of Data-Driven Decision-Making

Authors

  • Aarav Sharma Author
  • Priya Nair Author

DOI:

https://doi.org/10.61424/2vy91f33

Keywords:

Business Analytics Capability, Competitive Advantage, Data-Driven Decision-Making, Organizational Performance, Business Intelligence

Abstract

Business analytics capability has emerged as a critical organizational resource for firms seeking to strengthen competitive advantage in increasingly data-intensive and dynamic markets. This study examines the relationship between business analytics capability and competitive advantage, with particular emphasis on the mediating role of data-driven decision-making. The study adopts a comprehensive review approach, synthesizing findings from relevant empirical and conceptual literature on analytics capabilities, organizational decision-making, and firm performance. The reviewed evidence indicates that business analytics capability enables organizations to effectively collect, integrate, analyze, and interpret data, thereby improving the quality, speed, and accuracy of managerial decisions. Data-driven decision-making serves as an important mechanism through which analytics capabilities are translated into competitive outcomes by supporting evidence-based resource allocation, market responsiveness, operational efficiency, customer understanding, and innovation. The findings further suggest that organizations possessing advanced analytical capabilities do not automatically achieve superior performance; rather, competitive benefits are more likely when analytical insights are systematically incorporated into strategic and operational decision processes. The study therefore concludes that data-driven decision-making plays a significant mediating role in converting business analytics capability into sustainable competitive advantage. The review highlights the importance of developing not only technological and analytical infrastructure but also managerial competencies, data governance practices, and an organizational culture that supports evidence-based decision-making.

References

Adenike, A. (2018). Strengthening Financial Market Infrastructure in Emerging Economies: Lessons From Central Banking Operations. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 10(02), 177-182. https://doi.org/10.18090/samriddhi.v10i02.12

Adenike, A. (2023). Cashless Policy Transitions and Currency Substitution: Nigeria’s 2012-2022 Evolution Compared with Sweden, China, South Korea, and US Instant Payments Via Fednow. Research Journal in Business and Economics, 1(1), 236-247. https://doi.org/10.61424/rjbe.v1i1.925

Alam, M. I., Hemal, M. A. K. P., Sami, M. A., & Rahman, M. L. (2024). Robust and interpretable crop recommendation. European Journal of Ecology, Biology and Agriculture, 1(5), 168–184. https://doi.org/10.59324/ejeba.2024.1%285%29.14.

Alam, M. I., Sami, M. A., Al Masud, A., Ahmed, H., & Hossain, F. (2025). AI-driven big data analytics for personalized cancer treatment. Journal of Computer Science and Technology Studies, 7(11), 428–441. https://doi.org/10.32996/jcsts.2025.7.11.40.

Alam, M. I., Sami, M. A., Hemal, M. A. K. P., & Rahman, M. L. (2023). Predictive analytics and decision intelligence for climate-resilient agritech systems, 2(1), 44–56. https://doi.org/10.32996/agjcsts.2023.2.1.4.

Alam, M. I., Sikder, T. R., Sami, M. A., Rahman, M. L., et al. (2026). A robust and explainable approach to crop recommendation. Journal of Environmental and Agricultural Studies, 7(3), 1–15. https://doi.org/10.32996/jeas.2026.7.3.1.

Alasa, D. K., Hossain, D., Jiyane, G., Sarwer, M. H., & Saha, T. R. (2025b). AI-Driven Personalization in E-Commerce: The Case of Amazon and Shopify’s Impact on Consumer Behavior. Voice of the Publisher, 11(1), 104-116.https://doi.org/10.4236/vp.2025.111009

Alasa, D.K., Hossain, D., Jiyane, G. (2025a). Hydrogen Economy in GTL: Exploring the role of hydrogen-rich GTL processes in advancing a hydrogen-based economy. International Journal of Communication Networks and Information Security (IJCNIS), 17(1), 81–91. Retrieved from https://www.ijcnis.org/index.php/ijcnis/article/view/8021

Al-Khatib, A. W. (2022). Can big data analytics capabilities promote a competitive advantage? Green radical innovation, green incremental innovation and data-driven culture in a moderated mediation model. Business Process Management Journal, 28(4), 1025-1046.

Almazmomi, N., Ilmudeen, A., & Qaffas, A. A. (2022). The impact of business analytics capability on data-driven culture and exploration: achieving a competitive advantage. Benchmarking: An International Journal, 29(4), 1264-1283.

AL-Shboul, M. D. A. (2024). Do reliable big and cloud data analytics capabilities in manufacturing firms' supply chain boosting unique comparative advantage? A moderated-mediation model of data-driven competitive sustainability, green product innovation and green process innovation at North Africa region. International Journal of Productivity and Performance Management, 73(8), 2598-2628.

Aniwa S.C. (2021). Impact of Supply Chain Integration on Operational Performance: Insights from Manufacturing Firms in Emerging Economies. Iconic Research And Engineering Journals, 5(4).

Ayrin, F. J., Rahman, M. M., Quader, M. A., Dass, A., Khondaker, M. M. H., & Chakraborty, M. (2025). MentalLLM: A transformer-based large language model framework for depression detection. In 2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE). https://doi.org/10.1109/WIECON-ECE69386.2025.11525902

Bulbul, I. J., Zahir, Z., Ahmed, T., & Alam, P. (2019). Comparative study of the antimicrobial, minimum inhibitory concentrations (MIC), cytotoxic and antioxidant activity of methanolic extract of different parts of Phyllanthus acidus (L.) Skeels (family: Euphorbiaceae). World Journal of Pharmacy and Pharmaceutical Sciences, 8(1), 12–57. https://doi.org/10.20959/wjpps20191-10735

Cao, G., & Duan, Y. (2014). A path model linking business analytics, data-driven culture, and competitive advantage.

Das, K., Tanvir, A., Rani, S., & Aminuzzaman, F. M. (2025). Revolutionizing agro-food waste management: Real-time solutions through IoT and big data integration. Voice of the Publisher, 11(1), 17–36. https://doi.org/10.4236/vp.2025.111003

Garmaki, M., Gharib, R. K., & Boughzala, I. (2023). Big data analytics capability and contribution to firm performance: the mediating effect of organizational learning on firm performance. Journal of Enterprise Information Management, 36(5), 1161-1184.

Habib, M. R., Yusuf, M. A., Warnasuriya, W. M. H. N., Sunny, K., Rahaman, M. M., & Khan, M. R. K. (2024). A comprehensive review on the advancement of home automation system. In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) (pp. 638–642). IEEE. https://doi.org/10.1109/ICoICI62503.2024.10696135

Hasan, M. M., Alam, M. I., Chowdhury, M. A. H., & Anwar, M. M. (2026). AI-driven big data analytics for precision medicine and healthcare intelligence. Frontiers in Computer Science and Artificial Intelligence, 5(2), 41–62. https://doi.org/10.32996/jcsts.2026.5.1.5.

Hemal, M. A. K. P., Sayeed, N., Sami, M. A., Alam, M. I., Sikder, T. R., Dipa, S. A., & Rahman, M. L. (2025). Leveraging data analytics to strengthen public health and global economic sustainability. European Journal of Medical and Health Research, 3(4), 253–263. https://doi.org/10.59324/ejmhr.2025.3%284%29.37.

Hossain D., Alasa D.K, Jiyane G. (2023). Water-based fire suppression and structural fire protection: strategies for effective fire control. International Journal of Communication Networks and Information Security (IJCNIS). 15(4):485-94. Available from: https://ijcnis.org/index.php/ijcnis/article/view/7982.

Hossain D., Alasa D.K. (2024a). Numerical modeling of fire growth and smoke propagation in enclosure. Journal of Management World. (5):186-96. https://doi.org/10.53935/jomw.v2024i4.1051.

Hossain D., Alasa D.K. (2024b). Fire detection in gas-to-liquids processing facilities: challenges and innovations in early warning systems. International Journal of Biological, Physical and Chemical Studies. 6(2):7-13.https://doi.org/10.32996/ijbpcs.2024.6.2.2

Hossain, D. (2022). Fire dynamics and heat transfer: advances in flame spread analysis. Open Access Res J Sci Technol. 2022;6(2):70-5. https://doi.org/10.53022/oarjst.2022.6.2.0061.

Hossain, D. (2025). Water Efficient Suppression Material Fire Behaviour and AI Driven Safety in Future Fire Protection Research. EJSMT, 1(5), 62–76. https://doi.org/10.59324/ejsmt.2025.1(5).07

Hossain, D.(2021). A fire protection life safety analysis of multipurpose building. Available from: https://digitalcommons.calpoly.edu/fpe_rpt/135/.

Hossain, D., Asrafuzzaman, M., Dash, S., & Rani, S. (2024). Multi-Scale Fire Dynamics Modeling: Integrating Predictive Algorithms for Synthetic Material Combustion in Compartment Fires. Journal of Management World. (5): 363-374.https://doi.org/10.53935/jomw.v2024i4.1133

Hossain, M. J., Bakhsh, M. M., Sami, M. A., Alam, M. I., Melon, M. M. H., & Manik, M. M. T. G. (2026). Self-adaptive artificial intelligence systems for large-scale data-driven decision making. In 2026 IEEE I3CTCON (pp. 1–8). https://doi.org/10.1109/I3CTCON68242.2026.11507252.

Islam, A., & Jantan, A. H. B. (2023). The mediation effect of affective organizational commitment on the relationship between HRM practices and turnover intention in the RMG industry. Research Journal in Business and Economics, 1(1), 24-38.

Islam, A., Jantan, A. H. B., Khalifa, G. S., Islam, A., Islam, B., & Hossian, A. (2023). Effects of Decision Making and Work-life Balance on Productivity of Female Employees in the RMG Industry of Bangladesh. The Mediating Role of Work Motivation. Research Journal in Business and Economics, 1(1), 48-59.

Islam, M. A., & Sinniah, S. (2025). Exploring customer relationship management factors, customer trust, and innovation capacity: A quantitative study on customer retention. Accountancy Business and the Public Interest, 41(10), 12-29.

Islam, M. A., Islam, M. A., Amin, M. B., Hossain, M. M., Hassan, M. S., Afrin, S., & Oláh, J. (2025). Enhancing academic's performance: Exploring the interaction of innovative work behavior, intrinsic motivation, and self-efficacy in public universities. Social Sciences & Humanities Open, 12, 102210.

Kaur, J., Prabha, M., Samiun, M., Hasan, S. N., Hasan, R., Esa, H., et al. (2025). Comparative analysis of transformer and LSTM architectures for cybersecurity threat detection. EAI Endorsed Transactions on AI and Robotics, 4. https://publications.eai.eu/index.php/airo/article/view/9759.

Rahman, M. M., Juie, B. J. A., Tisha, N. T., & Tanvir, A. (2022). Harnessing predictive analytics and machine learning in drug discovery, disease surveillance, and fungal research. Eurasia Journal of Science and Technology, 4(2), 28-35. https://doi.org/10.61784/ejst3099

Rahman, M. M., Rahman, M. S., Islam, S., Khan, S. I., Ashik, A. A. M., Hossain, E., & Tanvir, A. (2025). Integrating data analytics into health informatics: Advancing equity, pharmaceutical outcomes, and public health decision-making. Eurasian Journal of Medicine and Oncology, 9(4), 284–295. https://doi.org/10.36922/EJMO025300319.

Rahman, M. M., Rahman, M. S., Islam, S., Khan, S. I., Ashik, A. A. M., Hossain, E., & Tanvir, A. (2025). Integrating data analytics into health informatics: Advancing equity, pharmaceutical outcomes, and public health decision-making. Eurasian Journal of Medicine and Oncology, 9(4), 284–295. https://doi.org/10.36922/EJMO025300319

Saha, P. P., Paul, R., Khan, M. R. K., Siddique, N. A. S., & Sarker, B. D. (2026). AI-driven modernization of Medicare and Medicaid enterprise systems: Interoperability, claims analytics, and fraud detection frameworks. Journal of Intelligent Decision Making and Information Science, 3(5s), 827–866. https://doi.org/10.59543/jidmis.v3.1223

Saha, P. P., Rahaman, M. M., Islam, M. T., & Chowdhury, N. I. (2025b). Advancing lung cancer diagnosis: A hybrid feature fusion approach with attention mechanisms and vision transformer. In 2025 2nd International Conference on Intelligent Systems for Cybersecurity (ISCS) (pp. 1–7). IEEE. https://doi.org/10.1109/ISCS69371.2025.11386016

Saha, P. P., Rone, P. D., Sarkar, D., Yusuf, M. A., Hossan, M. I., & Mazumder, M. S. J. (2025a). Advancing carbon emission prediction through machine learning: The impact of fossil, nuclear, and renewable energies. In 2025 International Conference on Emerging Smart Computing and Informatics (ESCI) (pp. 1–7). IEEE. https://doi.org/10.1109/ESCI63694.2025.10988213

Sami, M. A., Hemal, M. A. K. P., Alam, M. I., & Rahman, M. L. (2024). Data governance and analytics infrastructure for scalable decision-making. European Journal of Applied Science, Engineering and Technology, 2(2), 388–403. https://doi.org/10.59324/ejaset.2024.2%282%29.28.

Sami, M. A., Rahman, M. L., Tanni, Z. A., Munmun, Z. S., Nusrat, S., & Biswas, B. (2026). Artificial intelligence and big data for precision medicine. Frontiers in Computer Science and Artificial Intelligence, 5(6), 36–43. https://doi.org/10.32996/fcsai.2026.5.6.7.

Sarwer, M. H., Saha, T. R., & Hossain, D. (2022). Driving Business Innovation with Artificial Intelligence, Machine Learning and Blockchain Technology. Journal of Business and Management Studies, 4(3), 221-230. https://doi.org/10.32996/jbms.2022.4.3.21

Tanvir A, Jo J, Park SM. Targeting Glucose Metabolism: A Novel Therapeutic Approach for Parkinson's Disease. Cells. 2024 Nov 13;13(22):1876. doi: 10.3390/cells13221876. PMID: 39594624; PMCID: PMC11592965.

Tanvir, A., Juie, B. J. A., Tisha, N. T., & Rahman, M. M. (2020). Synergizing big data and biotechnology for innovation in healthcare, pharmaceutical development, and fungal research. International Journal of Biological, Physical and Chemical Studies, 2(2), 23–32. https://doi.org/10.32996/ijbpcs.2020.2.2.4

Vafaei-Zadeh, A., Madhuri, J., Hanifah, H., & Thurasamy, R. (2024). The interactive effects of capabilities and data-driven culture on sustained competitive advantage. IEEE Transactions on Engineering Management, 71, 8444-8458.

Yusuf, M. A., Chowdhury, N. M., Rone, P. D., Saha, P. P., Hossan, M. I., Sarkar, D., Paul, R., Hossain, M. R., & Chakraborty, M. (2025). Advancing Public Safety with Real-Time Life Jacket Detection and Demographic Profiling Using YOLOv8 and Age Classification. EAI Endorsed Trans AI Robotics. 4.1-12. https://doi.org/10.4108/airo.9785. Available from: https://publications.eai.eu/index.php/airo/article/view/978z5

Yusuf, M. A., Khan, M. R. K., Saha, P. P., & Rahaman, M. M. (2024). Data fusion of semantic and depth information in the context of object detection. In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) (pp. 1124–1129). IEEE. https://doi.org/10.1109/ICoICI62503.2024.10696627.

Zhang, P., & Thurasamy, R. (2024). Bridging big data analytics capability and competitive advantage in China’s agribusiness: The mediator of absorptive capacity. Systems, 13(1), 3.

Downloads

Published

2026-08-29