Optimizing Capital Allocation and Investment Decisions in the U.S. Economy Through Data Analytics
DOI:
https://doi.org/10.54536/ajase.v3i1.5698Keywords:
Capital Allocation, Data Analytics, Economic Growth, Investment Decisions, Machine LearningAbstract
Today, investment and capital location is a central mechanism of performance in the economic system, but conventional approaches tend to fall short in terms of managing resources, resulting in less than optimal conditions. In the interest of ever increasing availability of big data, advanced data analytics tools integration into capital allocation processes is underdeveloped. This research project fills the gap since it assesses how data analytics can be used to optimize the process of investment decision-making in the U.S. economy. To determine the effect of machine learning, predictive analytics and descriptive analytics tools on capital allocation performance, Return on Investment (ROI), market share change, and financial growth were the primary objectives. There were 300 sampled organizations (both in the public and the private sectors) and the data were gathered by way of surveys, along with secondary financial reports. The data analytics use and the effectiveness of capital allocation were analyzed through Pearson correlation, ANOVA, multiple regressions, and t-tests, as statistical methods. They showed that application of machine learning and predictive analytics was highly linked with the increment in ROI (mean = 19.2%, p < 0.01), the contribution to the growth of market share (mean = 4.8%, p < 0.01), and financial growth (mean = 12.6%, p < 0.01). Moreover, the organizations applying these tools demonstrated better performance in comparison with the ones that did not incorporate data analytics, even emphasizing the impressive role of advanced analytics in achieving better financial performance. These results indicate that a data-driven solution of multiple parties can complement capital allocation and provide high value on economic decisions. The study adds to an emerging knowledge on data analytics applied to economic decisions and aids policymakers and businesses interested in enhancing a company investment strategy.
Downloads
References
Abir, S. I., Sarwer, M. H., Hasan, M., Sultana, N., Dolon, M. S. A., Arefeen, S. S., ... & Saha, T. R. (2024). Accelerating BRICS economic growth: AI-driven data analytics for informed policy and decision making. Journal of Economics, Finance and Accounting Studies, 6(6), 102-115.
Adriaens, P., Tahvanainen, A., & Dixon, M. (2021). Smart infrastructure finance: Investment in data-driven industry ecosystems. In Green and social economy finance (pp. 192-225). CRC Press.
Aro, O. E. (2024). Predictive analytics in financial management: Enhancing decision-making and risk management. International Journal of Research Publication and Reviews, 5(10), 2181-2194.
Awan, U., Shamim, S., Khan, Z., Zia, N. U., Shariq, S. M., & Khan, M. N. (2021). Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance. Technological Forecasting and Social Change, 168, 120766.
Beck, R., Coppola, A., Lewis, A. J., Maggiori, M., Schmitz, M., & Schreger, J. (2024). The geography of capital allocation in the Euro Area (No. w32275). National Bureau of Economic Research.
Boone, T., Ganeshan, R., Jain, A., & Sanders, N. R. (2019). Forecasting sales in the supply chain: Consumer analytics in the big data era. International Journal of Forecasting, 35(1), 170-180.
Calder, K. E. (2021). Strategic capitalism: Private business and public purpose in Japanese industrial finance.
Challoumis, C. (2024). How AI insights are revolutionizing financial strategies for enterprises. In XIV International Scientific Conference (pp. 108-140).
Challoumis, C. (2024). Influence of historical investments on present economic conditions. SSRN Electronic Journal, 1-14.
Challoumis, C., & Eriotis, N. (2024). A historical analysis of the banking system and its impact on the Greek economy. Edelweiss Applied Science and Technology, 8(6), 1598-1617.
Erica, A., Gantari, L., Qurotulain, O., Nuche, A., & Sy, O. (2024). Optimizing decision-making: Data analytics applications in management information systems. APTISI Transactions on Management, 8(2), 115-122.
Fehrenbacher, D. D., Ghio, A., & Weisner, M. (2023). Advice utilization from predictive analytics tools: The trend is your friend. European Accounting Review, 32(3), 637-662.
Gade, K. R. (2021). Data-driven decision making in a complex world. Journal of Computational Innovation, 1(1).
Gintalas, M. (2022). The relationship between stock performance and financial ratios: An approach based on machine learning (Doctoral dissertation, Vilniaus universitetas).
Goodwin, N., Harris, J. M., Nelson, J. A., Rajkarnikar, P. J., Roach, B., & Torras, M. (2022). Macroeconomics in context. Routledge.
Haidari, M. N. (2023). Impact of decision-making on investment performance: A comprehensive analysis. Journal of Asian Development Studies, 12(4), 980-990.
Hossain, Q., Yasmin, F., Biswas, T. R., & Asha, N. B. (2024). Data-driven business strategies: A comparative analysis of data science techniques in decision-making. Sch J Econ Bus Manag, 9, 257-263.
Ikegwu, A. C., Nweke, H. F., Anikwe, C. V., Alo, U. R., & Okonkwo, O. R. (2022). Big data analytics for data-driven industry: A review of data sources, tools, challenges, solutions, and research directions. Cluster Computing, 25(5), 3343-3387.
Junaedi, J. (2024). Understanding the role of finance in sustainable development: A qualitative study on environmental, social, and governance (ESG) practices. Golden Ratio of Finance Management, 4(2), 113-130.
Lee, J. W. (2020). Big data strategies for government, society, and policy-making. The Journal of Asian Finance, Economics and Business, 7(7), 475-487.
Mekonnen, Z. A. (2024). Public health informatics: An overview. In Public Health Informatics: Implementation and Governance in Resource-Limited Settings (pp. 27-61).
Novak, A., Pravdyvets, O., Chornyi, O., Sumbaieva, L., Akimova, L., & Akimov, O. (2022). Financial and economic security in the field of financial markets at the stage of European integration. International Journal of Professional Business Review, 7(5), 24.
O’Neill, P. (2019). The financialisation of urban infrastructure: A framework of analysis. Urban Studies, 56(7), 1304-1325.
Ojika, F. U., Onaghinor, O. S. A. Z. E. E., Esan, O. J., Daraojimba, A. I., & Ubamadu, B. C. (2023). A predictive analytics model for strategic business decision-making: A framework for financial risk minimization and resource optimization. IRE Journals, 7(2), 764-766.
Olanrewaju, O. I. K., Daramola, G. O., & Ekechukwu, D. E. (2024). Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact. World Journal of Advanced Research and Reviews, 22(3), 564-573.
Olayinka, O. H. (2019). Leveraging predictive analytics and machine learning for strategic business decision-making and competitive advantage. International Journal of Computer Applications Technology and Research, 8(12), 473-486.
Owoade, S. J., Uzoka, A., Akerele, J. I., & Ojukwu, P. U. (2024). Enhancing financial portfolio management with predictive analytics and scalable data modeling techniques. International Journal of Applied Research in Social Sciences, 6(11), 2678-2690.
Pandya, J. B. (2024). Deep learning approach for stock market trend prediction and pattern finding (PhD thesis).
Rahaman, M. A., Rozony, F. Z., Mazumder, M. S. A., Haque, M. N., & Rauf, M. A. (2024). Big data-driven decision making in project management: A comparative analysis. Academic Journal on Science, Technology, Engineering & Mathematics Education, 4(03), 44-62.
Ramya, J., Yerraguravagari, S. S., Gaikwad, S., & Gupta, R. K. (2024). AI and machine learning in predictive analytics: Revolutionizing business strategies through big data insights. Library of Progress-Library Science, Information Technology & Computer, 44(3).
Ren, S. (2022). Optimization of enterprise financial management and decision-making systems based on big data. Journal of Mathematics, 2022(1), 1708506.
Rouf, N., Malik, M. B., Arif, T., Sharma, S., Singh, S., Aich, S., & Kim, H. C. (2021). Stock market prediction using machine learning techniques: A decade survey on methodologies, recent developments, and future directions. Electronics, 10(21), 2717.
Sarker, I. H. (2021). Data science and analytics: An overview from data-driven smart computing, decision-making, and applications perspective. SN Computer Science, 2(5), 377.
Sarkutė, L., Sina, D., Bello, K., & Vercuni, A. (2024). Strategic management decisions in the context of foreign direct investment: The role of institutions and economic determinants. Sustainable Regional Development Scientific Journal, 1(1), 40-54.
Sharma, R., & Mehta, K. (2024). Stock market predictions using deep learning: Developments and future research directions. In Deep Learning Tools for Predicting Stock Market Movements (pp. 89-121).
Tallat, R., Hawbani, A., Wang, X., Al-Dubai, A., Zhao, L., Liu, Z., ... & Alsamhi, S. H. (2023). Navigating Industry 5.0: A survey of key enabling technologies, trends, challenges, and opportunities. IEEE Communications Surveys & Tutorials, 26(2), 1080-1126.
Tan, T. M., & Saraniemi, S. (2023). Trust in blockchain-enabled exchanges: Future directions in blockchain marketing. Journal of the Academy of Marketing Science, 51(4), 914-939.
Trunk, A., Birkel, H., & Hartmann, E. (2020). On the current state of combining human and artificial intelligence for strategic organizational decision making. Business Research, 13(3), 875-919.
Udo, W. S., Ochuba, N. A., Akinrinola, O., & Ololade, Y. J. (2024). Theoretical approaches to data analytics and decision-making in finance: Insights from Africa and the United States. GSC Advanced Research and Reviews, 18(3), 343-349.
Weber, F. (2023). Business analytics and intelligence. In Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios (pp. 1-32). Wiesbaden: Springer Fachmedien Wiesbaden.
Wilenius, I. (2024). Utilization of artificial intelligence in investment decisions under market volatility: Manager vs. machine.
Wirawan, P. (2023). Leveraging predictive analytics in financing decision-making for comparative analysis and optimization. Advances in Management & Financial Reporting, 1(3), 157-169.
Zhu, X., & Yang, Y. (2021). Big data analytics for improving financial performance and sustainability. Journal of Systems Science and Information, 9(2), 175-191.
Zouo, S. J. C., & Olamijuwon, J. (2024). Financial data analytics in healthcare: A review of approaches to improve efficiency and reduce costs. Open Access Research Journal of Science and Technology, 12(2), 10-19
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Ismoth Zerine, Md Mainul Islam, Tauhedur Rahman, Morium Akter, Md Rakibul Haque Pranto

This work is licensed under a Creative Commons Attribution 4.0 International License.