Improvement of financial analysis of cluster activities
Abstract
This research paper addresses the critical need for an advanced framework to elevate the financial analysis of cluster activities. Clusters, defined as geographically proximate groups of interconnected companies and associated institutions in a particular field, have emerged as key drivers of economic growth. However, the existing financial analysis methods often fall short in capturing the complex dynamics and interdependencies within these clusters. The paper delves into the current challenges and limitations of conventional financial analysis in the context of cluster activities. It highlights the inadequacy of standard metrics in capturing the unique characteristics and synergies inherent in clusters, leading to suboptimal decision-making processes. By integrating data analytics, risk assessment models, and qualitative assessments, the framework aims to provide a holistic view of the financial landscape within clusters. Also explores the broader impact on regional economic development and the potential scalability of the framework across various industries. This research contributes to the ongoing discourse on financial analysis methodologies, specifically tailored for cluster activities. The proposed framework offers a sophisticated and practical solution to address the shortcomings of conventional approaches, thereby empowering stakeholders to make more informed decisions in the dynamic and interconnected landscape of cluster- based economies.