TACKLING ECONOMIC INEQUALITIES THROUGH BUSINESS ANALYTICS: A LITERATURE REVIEW

Abstract

This literature review delves into the intersection of business analytics and its potential to address economic inequalities. In an era where data-driven decision-making is becoming ubiquitous, this study explores how organizations leverage business analytics to analyze, understand, and mitigate economic disparities. The review encompasses a diverse range of scholarly articles, research papers, and case studies, providing insights into the strategies, methodologies, and impact of utilizing business analytics to tackle economic inequalities. It transitions into an exploration of the role that business analytics plays in this context, emphasizing the power of data-driven insights to inform and influence decision-makers in various sectors. Examining how predictive modeling techniques within business analytics contribute to identifying patterns and trends that inform strategic decision-making aimed at reducing economic inequalities. Investigating how business analytics is applied to formulate and assess the effectiveness of policies designed to address economic disparities, with a focus on evidence-based decision-making. Analyzing case studies that showcase how businesses leverage analytics to adopt more inclusive practices in areas such as hiring, promotions, and supply chain management, contributing to the reduction of economic inequalities. Examining the ethical dimensions of employing business analytics in the pursuit of reducing economic inequalities, including issues related to privacy, consent, and bias mitigation. The literature review concludes with a synthesis of findings, identifying gaps in current research and proposing avenues for future exploration. By synthesizing diverse perspectives, methodologies, and empirical evidence, this literature review contributes to a comprehensive understanding of how business analytics can serve as a powerful tool in the collective effort to tackle economic inequalities on a global scale. Keywords: Business Analytics, Inequalities, Bias Mitigation, Technological Advancement, Review.