A dynamic graph-based approach to ranking firms for identifying key players using inter-firm transactions

Abstract

Ranking firms in an inter-firm transaction network is a crucial task for identifying key players in an industry, thereby explaining the agglomeration of economic activities and assisting with competitor identification. To the best of our knowledge, despite the advantages of network-based approaches in market analysis, few studies have employed network analysis tools to rank firms. However, these studies failed to capture the characteristics of inter-firm transaction networks (i.e., evolving over time, having multiple edges between nodes, among others). In this study, we propose a new ranking method, FirmRank, that identifies key players based on centrality metrics in network analysis, leveraging inter-firm transactions to discern the characteristics of an inter-firm transaction network. Our proposed ranking method is evaluated using real-world datasets from a corporate information database, and the evaluation results demonstrate the superiority of our method over well-known ranking methods-PageRank and age-based PageRank.