Enhancing Load Capacity Factor: The Influence of Financial Accessibility, AI Innovation, and Institutional Quality in the United States

Authors

  • Shake Ibna Abir Department of Mathematics, Western Kentucky University, Bowling Green, KY, USA
  • Shaharina Shoha Department of Mathematics, Western Kentucky University, Bowling Green, KY, USA
  • Sarder Abdulla Al Shiam Department of Management -Business Analytics, St Francis College,USA
  • Md Shah Ali Dolon Department of Finance and Financial Analytics, University of New Haven, West Haven, United States
  • Shewly Bala Department of Finance, University of Dhaka, Dhaka 1000, Bangladesh https://orcid.org/0009-0002-6547-8366
  • Hemel Hossain Dhaka School of Bank Management, University of Dhaka, Bangladesh
  • Hasibur Rahman School of Business & Technology, Washington University of Virginia, 4300 Evergreen Ln, Annandale, VA 22003.
  • Afsana Akhter Department of Economics, Noakhali Science and Technology University, Sonapur, Noakhali-3814, Bangladesh
  • Mohammad Ridwan Department of Economics, Noakhali Science and Technology University
  • Robeena Bibi School of Public Administration, Hohai University, Nanjing China

DOI:

https://doi.org/10.56556/jescae.v3i4.979

Keywords:

AI Innovation, Financial Accessibility, Institutional Quality, Load Capacity Factor, United States

Abstract

The investigation analyzes the impact of financial accessibility, AI innovation, urbanization, and institutional quality on the load capacity factor in the United States from 1990 to 2019. A series of stationarity tests were conducted to detect the presence of unit root problems, revealing a mixed order of integration with no significant unit root issues. To explore the cointegration among variables, the ARDL bounds test was employed, confirming long-run cointegration. The ARDL model's short-run and long-run estimations demonstrate that the Load Capacity Curve hypothesis holds in the United States, with a U-shaped relationship between income and load capacity factor. The results also reveal that financial accessibility, AI innovation, and institutional quality positively influence the load capacity factor in both the short and long run. Conversely, urbanization significantly reduces the load capacity factor over both time horizons. Furthermore, the study utilized further approaches, including Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR), all of which validated the ARDL estimation results. Diagnostic tests confirmed the robustness of the model, showing that the variables are free from specification errors, serial correlation, and heteroscedasticity. These findings provide valuable insights for policymakers aiming to enhance load capacity through financial and technological advancements while considering the implications of urbanization.

Author Biographies

Shake Ibna Abir, Department of Mathematics, Western Kentucky University, Bowling Green, KY, USA

Shake Ibna Abir is currently pursuing a Master's degree in the Department of Mathematics at Western Kentucky University, located in Bowling Green, Kentucky, USA. His academic journey is focused on deepening his expertise in mathematical sciences, contributing to both theoretical and applied research. Shake's commitment to his studies reflects a strong dedication to advancing his knowledge in mathematics, with the aim of making meaningful contributions to the field. His affiliation with Western Kentucky University highlights his pursuit of academic excellence and his aspiration to impact the broader mathematical community.

Shaharina Shoha, Department of Mathematics, Western Kentucky University, Bowling Green, KY, USA

Shaharina Shoha is currently pursuing a Master's degree in the Department of Mathematics at Western Kentucky University, located in Bowling Green, Kentucky, USA. Her academic journey is focused on deepening her expertise in mathematical sciences, contributing to both theoretical and applied research. Her commitment to her studies reflects a strong dedication to advancing her knowledge in mathematics, with the aim of making meaningful contributions to the field.

Sarder Abdulla Al Shiam, Department of Management -Business Analytics, St Francis College,USA

Sarder Abdulla Al Shiam is currently pursuing a Master's degree in the Department of Management with a focus on Business Analytics at St. Francis College, USA. His academic interests lie in harnessing data-driven strategies to solve complex business problems. Sarder is dedicated to mastering the skills required for effective decision-making and analysis in the modern business landscape. His affiliation with St. Francis College underscores his commitment to academic and professional excellence, as he aims to contribute valuable insights to the field of business analytics.

Md Shah Ali Dolon, Department of Finance and Financial Analytics, University of New Haven, West Haven, United States

Md Shah Ali Dolon is currently pursuing a Master's degree in the Department of Finance and Financial Analytics at the University of New Haven, located in West Haven, United States. His academic focus lies in the intersection of finance and data analysis, where he is developing the skills necessary to navigate and analyze complex financial markets. Md Shah Ali Dolon is committed to leveraging advanced analytics to drive financial decision-making and strategy. His affiliation with the University of New Haven underscores his dedication to academic excellence and his aspiration to contribute to the field of finance and analytics.

Hasibur Rahman, School of Business & Technology, Washington University of Virginia, 4300 Evergreen Ln, Annandale, VA 22003.

Hasibur Rahman is currently pursuing a Master's degree at the School of Business & Technology, Washington University of Virginia, located in Annandale, Virginia. His academic journey is focused on gaining in-depth knowledge and skills in business and technology, preparing him for the challenges of the modern professional world. Hasibur is dedicated to understanding the dynamic interplay between business strategies and technological advancements, aiming to contribute innovative solutions in these fields. His affiliation with Washington University of Virginia reflects his commitment to academic excellence and his ambition to make a significant impact in the business and technology sectors.

Afsana Akhter, Department of Economics, Noakhali Science and Technology University, Sonapur, Noakhali-3814, Bangladesh

Afsana Rinky is a graduate from the Department of Economics at Noakhali Science and Technology University. She is currently involved in the fields of data analysis and research, where she applies her strong analytical skills to explore economic trends and patterns. Afsana's academic background and hands-on experience in research make her a valuable contributor to various projects, as she continuously seeks to deepen her understanding of economic phenomena through data-driven approaches. Her work reflects a dedication to advancing knowledge in economics and related disciplines.

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Published

2024-10-26

How to Cite

Abir, S. I., Shoha, S., Abdulla Al Shiam, S., Dolon, M. S. A., Shewly Bala, Hemel Hossain, … Robeena Bibi. (2024). Enhancing Load Capacity Factor: The Influence of Financial Accessibility, AI Innovation, and Institutional Quality in the United States. Journal of Environmental Science and Economics, 3(4), 12–36. https://doi.org/10.56556/jescae.v3i4.979

Issue

Early Access

Section

Research Article

License

Creative Commons License

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

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