Abstract

The literature review on using mathematical models in strategic decision-making for business growth and sustainability explores existing studies on applying mathematical models in business decision-making. Mathematical models are increasingly popular in the business world, as they allow decision-makers to make informed and data-driven decisions, minimizing the risks associated with making decisions based on intuition or incomplete information. The materials used in this review are academic papers and research articles that use mathematical models in strategic decision-making for business growth and sustainability. The search for these materials involved using various academic databases, such as Google Scholar, Scopus, and Web of Science. The journals analyzed were 23 spanning the last ten years (2014 to 2023). The methods used in this review include a systematic approach to searching, screening, and selecting relevant literature, as well as a critical appraisal of the quality and relevance of the selected articles. The review also involved synthesizing and analyzing the selected articles' findings to identify key themes, patterns, and trends related to using mathematical models in strategic decision-making for business growth and sustainability. The various mathematical models that have been applied in business decision-making include statistical models, simulation models, optimization models, and predictive models. It also investigates the challenges and limitations of using mathematical models in business decision-making, such as data availability and quality, the models' complexity, and the need for specialized skills and expertise. The literature review on using mathematical models in strategic decision-making for business growth and sustainability highlights the growing importance of data-driven decision-making in the business world. The use of mathematical models can help organizations to make informed decisions that are based on reliable data and analysis and can lead to improved business performance and sustainability.