An integral financial indicator approach to ranking technology service companies: An empirical analysis

Abstract

This paper develops a sector-adaptive integral financial indicator framework for evaluating and ranking technology service companies. While composite indices are widely used in financial performance analysis, existing approaches remain largely sector-neutral, overlook the directional heterogeneity of financial indicators, and rely on single aggregation structures, potentially leading to biased or incomplete assessments. To address these limitations, the paper proposes a multidimensional composite index that integrates profitability, leverage, and capital structure within a unified analytical framework. The methodology introduces three key innovations: (i) a sector-specific design tailored to the financial characteristics of technology service firms, (ii) a direction-sensitive normalization procedure that explicitly distinguishes between beneficial and non-beneficial indicators, and (iii) a dual aggregation structure combining additive and geometric methods to evaluate compensatory and non-compensatory effects. The proposed approach is applied to a longitudinal dataset of leading technology service companies over the period 2012–2024. The results reveal substantial heterogeneity in financial performance, with a clear differentiation between improving, stable, and at-risk firms. The analysis also demonstrates that aggregation structure and indicator directionality significantly influence ranking outcomes, underscoring the importance of methodological design in composite index construction. Robustness and sensitivity analyses confirm the stability and reliability of the proposed framework. The study contributes to the literature by advancing composite index methodology through a sector-adaptive and directionally consistent approach, while providing a transparent and replicable tool for firm ranking. From a practical perspective, the framework offers valuable implications for investors, analysts, and policymakers by enabling more accurate benchmarking and informed decision-making in technology-driven markets.