Exploring Application of Mathematical Modeling in Organizational Decision-Making

Abstract

Focusing on its efficiency, challenges, and prospects for wider adoption, this research examines the application of mathematical modeling in decision-making within Nigerian organizations. In many diverse sectors, mathematical modelling provides a disciplined structure for decision makers to maximise operations, project results, and improve strategic decisions. Despite their advantages, many undeveloped countries—including Nigeria—have limited acceptance of mathematical models because of organisational opposition, insufficient technical understanding, and restricted tool availability. Combining formal questionnaires with interviews with professionals in the manufacturing, shipping, and finance sectors, the study reveals that linear programming and forecasting models are the most often used methods; most respondents say these models greatly increase the efficacy of decision-making. Meanwhile, lack of qualified people, inadequate software, and poor data quality turned out to be the main challenges to more general deployment. The study concludes that, although mathematical models can improve corporate decision-making, their general acceptability depends on overcoming technological, structural, and cultural constraints. Advice includes funding evidence-based decision-making, data management system improvement, and training courses. This paper provides realistic guidance for practitioners and legislators to enhance the integration of mathematical modelling in business operations and help them understand its purpose in decision-making.