Inter-company comparison using modified TOPSIS with objective weights

Abstract

Abstract Simultaneous consideration of multiple financial ratios is required to adequately evaluate and rank the relative performance of competing companies. This paper formulates the inter-company comparison process as a multi-criteria analysis model, and presents an effective approach by modifying TOPSIS for solving the problem. The modified TOPSIS approach can identify the relevance of the financial ratios to the evaluation result, and indicate the performance difference between companies on each financial ratio. To ensure that the evaluation result is not affected by the inter-dependence of the financial ratios, objective weights are used. As a result, the comparison process is conducted on a commonly accepted basis and is independent of subjective preferences of various stakeholders. An empirical study of a real case in China is conducted to illustrate how the approach is used for the inter-company comparison problem. The result shows that the approach can reflect the decision information emitted by the financial ratios used. The comparison of objective weighting methods suggests that, with the modified TOPSIS approach, the entropy measure compares favourably with other methods for the case study conducted. Scope and purpose The performance evaluation and ranking of modern enterprises is a complex process, in which multiple financial ratios are required to be considered simultaneously. The purpose of this paper is to apply the framework of multi-criteria analysis to the inter-company comparison problem. An effective approach based on the concept used by the technique for order preference by similarity to ideal solution (TOPSIS) is developed to rank competing companies in terms of their overall performance on multiple financial ratios. The approach modifies the TOPSIS method by using weighted Euclidean distances to ensure a meaningful interpretation of the evaluation result. The use of objective weights for financial ratios based on Shannon's entropy concept reflects the context-dependent concept of informational importance. This ensures that the evaluation result is not affected by the inter-dependency of criteria and inconsistency of subjective weights. This approach is particularly applicable for situations where reliable subjective weights cannot be obtained. With its simplicity in both concept and computation, the approach can readily be incorporated into a computer-based system.