EVALUATING COMPETITIVENESS ACROSS PUBLICLY LISTED COMPANIES USING KEY FINANCIAL METRICS: A DATA-DRIVEN APPROACH

Abstract

In an increasingly competitive global marketplace, assessing corporate competitiveness through financial metrics is vital for investors, analysts, and policymakers. This study proposes a structured, data-driven framework to evaluate the competitiveness of publicly listed companies using key financial indicators. Specifically, it examines revenue, earnings, net profit margin, price-to-earnings (P/E) ratio, price-to-sales (P/S) ratio, earnings per share (EPS), earnings yield (EY), and dividend yield (DY). Data were sourced from a global dataset of 9,912 firms, refined to 4,256 companies post-cleaning. The study employed benchmarking via median and interquartile range (IQR) analysis to mitigate outlier distortion, classify company performance, and enable fair cross-comparison across firm sizes and sectors. Findings highlight strong correlations between revenue and earnings, and between P/E and P/S ratios, whereas relationships among EPS, EY, and DY were weaker. Diagnostic charts and comparative analysis revealed that large-cap and mid-cap firms typically outperformed smaller firms, though no single metric could holistically define competitiveness. Only two companies—BAWAN Group and Samsung Electro-Mechanics—met the refined criteria for high competitiveness across multiple metrics. This research contributes a replicable benchmarking methodology that integrates statistical and visual analytics to support informed investment decisions. It also addresses gaps in comparative financial assessment frameworks, especially for emerging markets. Future studies are encouraged to expand the dataset temporally and sectorally to further refine the model and enhance predictive utility.