Utilizing Permutation and Combination Techniques in Business Decision-Making Processes

Crossmark

Main Article Content


Abstract

Although permutations and combinations are often regarded as purely theoretical mathematical topics, they play a significant role in practical decision-making and contemporary business operations. This study examines the application of permutations and combinations in everyday decision-making and real business contexts, particularly in quality control, marketing strategy, resource planning, and inventory management. Using real-world examples and case studies, the article demonstrates how organizations employ these combinatorial concepts to improve productivity, reduce costs, optimize available resources, and strengthen competitive advantage in increasingly complex market environments. The findings indicate that a sound understanding of permutations and combinations enhances managerial and executive decision-making, especially when evaluating numerous alternatives, assessing the likelihood of possible outcomes, selecting appropriate combinations of people or products, and determining optimal configurations. The study concludes that permutations and combinations are not merely academic concepts but practical analytical tools that support more effective and strategic business decisions. This study contributes to a broader understanding of how foundational mathematical reasoning can be applied to improve organizational efficiency and decision quality in business practice.

Downloads

Download data is not yet available.

Citation Metrics & Similar Scopus Articles

Data source Crossref
0
citations
Citation counts are source-specific and may differ because database coverage, reference matching, and update schedules are different. Counts are not added together. Crossref values represent citation links registered and matched by Crossref.
Check Secondary Documents in Scopus
Open this article in Scopus, then check the Secondary documents tab. Use Manual Citation Fallback only for counts you have verified manually.
Open in Scopus
Similar Scopus Articles
Scopus
  1. Morita Y. (2027)
    Clinical Outcomes of Antrectomy for Patients With Multiple Type I Gastric Neuroendocrine Tumors: A Case Series
    Den Open, 7(1)
  2. Nagasawa Y. (2027)
    Gastric Metastasis of Uterine Leiomyosarcoma Detected During Surveillance Endoscopy and Resected by Endoscopic Submucosal Dissection After Multiple Metachronous Metastases: A Case Report
    Den Open, 7(1)
  3. Maehara K. (2027)
    Mechanism of Fibrotic Anastomosis Formation in Endoscopic Ultrasound-guided Hepaticogastrostomy Using a Plastic Stent: Insights From an Autopsy Case of Perihilar Cholangiocarcinoma
    Den Open, 7(1)

Article Details

How to Cite
Sah, B., Jayswal, R., Thakur, S., Shah, N., Sah, D. K., & Sahani, S. K. (2026). Utilizing Permutation and Combination Techniques in Business Decision-Making Processes. Mikailalsys Journal of Mathematics and Statistics, 4(2), 199-220. https://doi.org/10.58578/mjms.v4i2.9336

References

Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2023). Quantitative methods for business (14th ed.). Cengage Learning.
Baker, K. R., & Trietsch, D. (2013). Principles of sequencing and scheduling. John Wiley & Sons.
Bell, S. T. (2007). Deep-level composition variables as predictors of team performance: A meta-analysis. Journal of Applied Psychology, 92(3), 595–615. https://doi.org/10.1037/0021-9010.92.3.595
Biggs, N. L. (1979). The roots of combinatorics. Historia Mathematica, 6(2), 109–136. https://doi.org/10.1016/0315-0860(79)90074-0
Chandon, P., Hutchinson, J. W., Bradlow, E. T., & Young, S. H. (2009). Does in-store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase. Journal of Marketing, 73(6), 1–17. https://doi.org/10.1509/jmkg.73.6.1
Chen, J. C., & Lee, W. C. (2018). Scheduling optimization in manufacturing systems using permutation-based algorithms. International Journal of Production Research, 56(4), 1456–1472.
Cook, W. J. (2012). In pursuit of the traveling salesman: Mathematics at the limits of computation. Princeton University Press.
DeMiguel, V., Garlappi, L., & Uppal, R. (2009). Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy? The Review of Financial Studies, 22(5), 1915–1953. https://doi.org/10.1093/rfs/hhm075
Elton, E. J., Gruber, M. J., Brown, S. J., & Goetzmann, W. N. (2019). Modern portfolio theory and investment analysis (10th ed.). John Wiley & Sons.
Hanssens, D. M. (Ed.). (2015). Empirical generalizations about marketing impact (2nd ed.). Marketing Science Institute.
Hillier, F. S., & Lieberman, G. J. (2021). Introduction to operations research (11th ed.). McGraw-Hill Education.
Hopkins, B., & Wilson, R. J. (2004). The truth about Königsberg. The College Mathematics Journal, 35(3), 198–207. https://doi.org/10.1080/07468342.2004.11922073
Mathieu, J. E., Tannenbaum, S. I., Donsbach, J. S., & Alliger, G. M. (2014). A review and integration of team composition models: Moving toward a dynamic and temporal framework. Journal of Management, 40(1), 130–160. https://doi.org/10.1177/0149206313503014
Montgomery, D. C. (2020). Introduction to statistical quality control (8th ed.). John Wiley & Sons.
Schrijver, A. (2005). On the history of combinatorial optimization (till 1960). In K. Aardal, G. L. Nemhauser, & R. Weismantel (Eds.), Handbook of discrete optimization (pp. 1–68). Elsevier. https://doi.org/10.1016/S0927-0507(05)12001-5
Simchi-Levi, D., Kaminsky, P., & Simchi-Levi, E. (2014). Designing and managing the supply chain (4th ed.). McGraw-Hill Education.
Stadtler, H. (2015). Supply chain management: An overview. In H. Stadtler, C. Kilger, & H. Meyr (Eds.), Supply chain management and advanced planning: Concepts, models, software, and case studies (pp. 3–28). Springer. https://doi.org/10.1007/978-3-642-55309-7_1
Wedel, M., & Kamakura, W. A. (2012). Market segmentation: Conceptual and methodological foundations (2nd ed.). Springer.