Modeling Enterprise Risk Management Ecosystems Using Text Analytics

In recent years, a paradigm shift in risk management has altered in a holistic way, which we call Enterprise Risk Management (ERM). ERM solves the limitations of Traditional Risk Management (TRM). Although firms perceive several benefits of ERM, the successful implementation of ERM rests upon institutional and contingency factors. The ERM approach then seeks to integrate the core system and processes of the firm rather than acting through silo perspective. With this in mind, this research applies text mining techniques to analyze bibliometric data from SCOPUS to propose the suitable ERM ecosystem. This longitudinal study uses 725 reliable documents across 26 years. The descriptive analysis relating to the journal, citation, author, and article performance is displayed. Text co-occurrence analysis of author keywords represented by network mapping shows five ecosystems that significantly integrate with ERM: (1) three lines of defense (3LOD), (2) corporate governance, (3) ERM framework, (4) firm culture, and (5) value creation. Ultimately, the hidden insight from the bibliometric data shows the correlation between ERM and modern firm direction such as sustainability.