DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.
Title: Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact
Authors: Luther Kington Nwobodo, Chioma Susan Nwaimo, Mayokun Daniel Adegbola
Journal: International journal of management & entrepreneurship research
Year: 2024
Volume: 6
Issue: 6
Language: en
In the context of escalating environmental concerns and the transition towards a greener economy, sustainable energy investments have emerged as a pivotal area for financial growth and innovation. This paper outlines a strategic framework for financial decision-making in sustainable energy investments, emphasizing the transformative role of big data. By integrating big data analytics into the investment process, stakeholders can enhance market analysis, risk assessment, performance monitoring, and predictive modeling, leading to more informed and effective investment strategies. The paper delves into various big data sources, analytical tools, and technologies that facilitate the collection, processing, and interpretation of vast amounts of information. Additionally, it presents case studies illustrating successful applications of big data in solar and wind energy projects, highlighting best practices and common challenges. The discussion extends to future trends, including advancements in artificial intelligence and machine learning, which are poised to further revolutionize the sector. The paper concludes with strategic recommendations for developing a data-driven investment approach, building robust data infrastructures, and fostering a culture of continuous learning and adaptation. By leveraging big data, investors can maximize the impact of their investments, drive sustainable growth, and contribute to the global energy transition.
Keywords:  Sustainable Energy Investments, Big Data Analytics, Strategic Financial Decision-Making, Market Analysis, Risk Assessment, Predictive Modeling.
Loading PDF...
Loading Statistics...