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Research Article

Advancements in Retail Price Optimization: Leveraging Machine Learning Models for Profitability and Competitiveness

Authors

  • Mohammad Anisur Rahman Department of Marketing & Business Analytics, Texas A&M University-Commerce, USA
  • Chinmoy Modak Information Technology, Craven Community College, USA
  • Md Abu Sufian Mozumder College of Business, Westcliff University, Irvine, California, USA
  • Mohammed Nazmul Islam Miah Department of Management Science and Quantitative Methods, Gannon University, USA
  • Mehedi Hasan Master of Science, Management- Business Analytics, St. Francis College, USA
  • Md Murshid Reja Sweet Department of Management Science and Quantitative Methods, Gannon University, USA
  • Syeda Farjana Farabi Doctor of Business Administration, Westcliff University, Irvine, California
  • Md Zikar Hossan Master of Business Administration in Management Information System, International American University Los Angeles
  • Mani Prabha Department of Business Administration, International American University, Los Angeles, California
  • Mahfuz Alam Department of Business Administration, International American University, Los Angeles, California

Abstract

Retail price optimization is essential for maximizing profitability and maintaining competitiveness in today's dynamic retail landscape. This study addresses retail price optimization as a regression problem, utilizing machine learning models to predict optimal price points for products. Leveraging factors such as product attributes, competitor pricing dynamics, and customer behaviors, regression analysis provides a structured approach to understanding the intricate relationships between variables. Among various regression techniques, the Random Forest Regressor emerges as a potent strategy, offering robustness and versatility in tackling complex pricing tasks. Results indicate that Random Forest outperforms Decision Tree and Logistic Regression models regarding accuracy, precision, recall, and overall predictive performance. With Random Forest achieving an accuracy of 94%, it demonstrates superior capability in capturing complex data patterns and making accurate predictions of retail prices. By leveraging advanced analytics and machine learning techniques, retailers can optimize pricing strategies, maximize profits, and maintain competitiveness in the market. This study underscores the importance of continuously analyzing and refining pricing strategies to gain a competitive edge in the retail landscape.

Article information

Journal

Journal of Business and Management Studies

Volume (Issue)

6 (3)

Pages

103-110

Published

2024-05-23

How to Cite

Mohammad Anisur Rahman, Chinmoy Modak, Md Abu Sufian Mozumder, Mohammed Nazmul Islam Miah, Mehedi Hasan, Md Murshid Reja Sweet, Syeda Farjana Farabi, Md Zikar Hossan, Mani Prabha, & Mahfuz Alam. (2024). Advancements in Retail Price Optimization: Leveraging Machine Learning Models for Profitability and Competitiveness. Journal of Business and Management Studies, 6(3), 103–110. https://doi.org/10.32996/jbms.2024.6.3.11

References

Al Shiam, S. A., Hasan, M. M., Nayeem, M. B., Choudhury, M. T. H., Bhowmik, P. K., Shochona, S. A., ... & Islam, M. R. (2024). Deep Learning for Enterprise Decision-Making: A Comprehensive Study in Stock Market Analytics. Journal of Business and Management Studies, 6(2), 153-160.

Al Shiam, S. A., Hasan, M. M., Nayeem, M. B., Choudhury, M. T. H., Bhowmik, P. K., Shochona, S. A., ... & Islam, M. R. (2024). Deep Learning for Enterprise Decision-Making: A Comprehensive Study in Stock Market Analytics. Journal of Business and Management Studies, 6(2), 153-160.

Amin, M. S., Ayon, E. H., Ghosh, B. P., MD, M. S. C., Bhuiyan, M. S., Jewel, R. M., & Linkon, A. A. (2024). Harmonizing Macro-Financial Factors and Twitter Sentiment Analysis in Forecasting Stock Market Trends. Journal of Computer Science and Technology Studies, 6(1), 58-67.

Al Shiam, S. A., Hasan, M. M., Pantho, M. J., Shochona, S. A., Nayeem, M. B., Choudhury, M. T. H., & Nguyen, T. N. (2024). Credit Risk Prediction Using Explainable AI. Journal of Business and Management Studies, 6(2), 61-66.

Bhuiyan, M. S., Chowdhury, I. K., Haider, M., Jisan, A. H., Jewel, R. M., Shahid, R., ... & Siddiqua, C. U. (2024). Advancements in Early Detection of Lung Cancer in Public Health: A Comprehensive Study Utilizing Machine Learning Algorithms and Predictive Models. Journal of Computer Science and Technology Studies, 6(1), 113-121.

Bhuiyan, M. (2024). Carbon Footprint Measurement and Mitigation Using AI (March 3, 2024). Available at SSRN: https://ssrn.com/abstract=4746446 or http://dx.doi.org/10.2139/ssrn.4746446

Chowdhury, M. S., Nabi, N., Rana, M. N. U., Shaima, M., Esa, H., Mitra, A., ... & Naznin, R. (2024). Deep Learning Models for Stock Market Forecasting: A Comprehensive Comparative Analysis. Journal of Business and Management Studies, 6(2), 95-99.

Chowdhury, M. S., Nabi, N., Rana, M. N. U., Shaima, M., Esa, H., Mitra, A., ... & Naznin, R. (2024). Deep Learning Models for Stock Market Forecasting: A Comprehensive Comparative Analysis. Journal of Business and Management Studies, 6(2), 95-99.

Chowdhury, M. S., Nabi, N., Rana, M. N. U., Shaima, M., Esa, H., Mitra, A., ... & Naznin, R. (2024). Deep Learning Models for Stock Market Forecasting: A Comprehensive Comparative Analysis. Journal of Business and Management Studies, 6(2), 95-99.

Ding H. (2022). Prediction of Retail Price of Sporting Goods Based on LSTM Network. Comput Intell Neurosci. Jul 9; 2022:4298235. doi: 10.1155/2022/4298235. PMID: 35855800; PMCID: PMC9288340.

Esa, H., Rahman, M. A., Mozumder, M. A. S., Gurung, N., Miah, M. N. I., Sweet, M. M. R., ... & Sabuj, M. S. H. (2024). Transformative Impact of Deep Learning in Stock Market Decision-Making: A Comparative Study of Convolutional Neural Networks. Journal of Business and Management Studies, 6(3), 28-34.

Ferdus, M. Z., Anjum, N., Nguyen, T. N., Jisan, A. H., & Raju, M. A. H. (2024). The Influence of Social Media on Stock Market: A Transformer-Based Stock Price Forecasting with External Factors. Journal of Computer Science and Technology Studies, 6(1), 189-194.

Ghosh, B. P., Bhuiyan, M. S., Das, D., Nguyen, T. N., Jewel, R. M., Mia, M. T., ... & Shahid, R. (2024). Deep Learning in Stock Market Forecasting: Comparative Analysis of Neural Network Architectures Across NSE and NYSE. Journal of Computer Science and Technology Studies, 6(1), 68-75.

Jewel, R. M., Linkon, A. A., Shaima, M., Sarker, M. S. U., Shahid, R., Nabi, N., ... & Hossain, M. J. (2024). Comparative Analysis of Machine Learning Models for Accurate Retail Sales Demand Forecasting. Journal of Computer Science and Technology Studies, 6(1), 204-210.

Jewel, R. M., Linkon, A. A., Shaima, M., Sarker, M. S. U., Shahid, R., Nabi, N., ... & Hossain, M. J. (2024). Comparative Analysis of Machine Learning Models for Accurate Retail Sales Demand Forecasting. Journal of Computer Science and Technology Studies, 6(1), 204-210.

Jewel, R. M., Chowdhury, M. S., Al-Imran, M., Shahid, R., Puja, A. R., Ray, R. K., & Ghosh, S. K. (2024). Revolutionizing Organizational Decision-Making for Stock Market: A Machine Learning Approach with CNNs in Business Intelligence and Management. Journal of Business and Management Studies, 6(1), 230-237.

Linkon, A. A., Shaima, M., Sarker, M. S. U., Nabi, N., Rana, M. N. U., Ghosh, S. K., ... & Chowdhury, F. R. (2024). Advancements and Applications of Generative Artificial Intelligence and Large Language Models on Business Management: A Comprehensive Review. Journal of Computer Science and Technology Studies, 6(1), 225-232.

Linkon, A. A., Shaima, M., Sarker, M. S. U., Nabi, N., Rana, M. N. U., Ghosh, S. K., ... & Chowdhury, F. R. (2024). Advancements and Applications of Generative Artificial Intelligence and Large Language Models on Business Management: A Comprehensive Review. Journal of Computer Science and Technology Studies, 6(1), 225-232.

Mia, M. T., Ferdus, M. Z., Rahat, M. A. R., Anjum, N., Siddiqua, C. U., & Raju, M. A. H. (2024). A Comprehensive Review of Text Mining Approaches for Predicting Human Behavior using Deep Learning Method. Journal of Computer Science and Technology Studies, 6(1), 170-178.

Nabi, N., Pabel, M. A. H., Rahman, M. A., Mozumder, M. A. S., Al-Imran, M., Sweet, M. M. R., ... & Sharif, M. K. (2024). Unleashing Deep Learning: Transforming E-commerce Profit Prediction with CNNs. Journal of Business and Management Studies, 6(2), 126-131.

Nabi, N., Pabel, M. A. H., Rahman, M. A., Mozumder, M. A. S., Al-Imran, M., Sweet, M. M. R., ... & Sharif, M. K. (2024). Unleashing Deep Learning: Transforming E-commerce Profit Prediction with CNNs. Journal of Business and Management Studies, 6(2), 126-131.

Ray, R. K., Linkon, A. A., Bhuiyan, M. S., Jewel, R. M., Anjum, N., Ghosh, B. P., ... & Shaima, M. (2024). Transforming Breast Cancer Identification: An In-Depth Examination of Advanced Machine Learning Models Applied to Histopathological Images. Journal of Computer Science and Technology Studies, 6(1), 155-161.

Rana, M. N. U., Al Shiam, S. A., Shochona, S. A., Islam, M. R., Asrafuzzaman, M., Bhowmik, P. K., ... & Asaduzzaman, M. (2024). Revolutionizing Banking Decision-Making: A Deep Learning Approach to Predicting Customer Behavior. Journal of Business and Management Studies, 6(3), 21-27.

Ray, R. K., Linkon, A. A., Bhuiyan, M. S., Jewel, R. M., Anjum, N., Ghosh, B. P., ... & Shaima, M. (2024). Transforming Breast Cancer Identification: An In-Depth Examination of Advanced Machine Learning Models Applied to Histopathological Images. Journal of Computer Science and Technology Studies, 6(1), 155-161.

Shaima, M., Nabi, N., Rana, M. N. U., Linkon, A. A., Sarker, M. S. U., Anjum, N., & Esa, H. (2024). Machine Learning Models for Predicting Corticosteroid Therapy Necessity in COVID-19 Patients: A Comparative Study. Journal of Computer Science and Technology Studies, 6(1), 217-224.

Shahid, R and Usuf A (n.d). Secured Crowd-Sourced Platform for Civic Engagement: My City Project."

Sayed, M. A., & Anjum, N. (n.d). Plug-In Architecture as Software Extension Mechanism: An Extensive Study of Eclipse Architecture.

Syed, M. A., & Anjum, N. (n.d). Embracing Transformative Trends: Leveraging Generative AI in Healthcare for Precision Medicine and Ethical Advancement.

Sina G., Erfan Z., Reza S and Shib S. S. (2023). Using deep learning to enhance business intelligence in organizational management[J]. Data Science in Finance and Economics, 3(4): 337-353. doi: 10.3934/DSFE.2023020

Saikat, M. H., Avi, S. P., Islam, K. T., Tahmina, T., Abdullah, M. S., & Imam, T. (2024). Real-Time Vehicle and Lane Detection using Modified OverFeat CNN: A Comprehensive Study on Robustness and Performance in Autonomous Driving. Journal of Computer Science and Technology Studies, 6(2), 30-36.

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Keywords:

Retail Price Optimization; Machine Learning; Profitability; Competitiveness