Unravelling Economic Complexity: A Systematic Exploration of Themes and Trends through Literature and Keyword Network Analysis

Background: The Economic Complexity Index (ECI) is a robust and computationally viable measure that captures the diversity and sophistication of an economy's industrial sector, reflecting the knowledge and capabilities embedded in its export basket. The rapid growth in scholarly literature employing economic complexity measures necessitates a systematic review of how ECI has been studied, applied, and understood by economists, policymakers, and researchers. Objectives: This study synthesises 215 “Economic Complexity†articles published in Web of Science (WoS) journals from 2006 to 2022. Methods/Approach: Using Systematic Literature Network Analysis (SLNA) and Keyword Network Exploration (KNE), the review identifies key trends, critical issues, and emerging topics in the field. SLNA integrates bibliographic networks with systematic literature reviews, while KNE explores thematic interconnections through keyword co-occurrence analysis. Open-source tools such as Sci2, Pajek, Biblioshiny (R-Package), and VOSviewer facilitated network extraction and analysis. Results: The findings highlight future research directions, including innovation, regional studies, institutions, human capital formation, ecological footprint, and firm-level economic complexity. Conclusions: This research provides essential insights into the development of economic complexity studies and outlines a pathway for future exploration.