BIBLIOMETRIC REVIEW OF SYSTEM DYNAMICS APPLICATIONS IN ECONOMICS AND FINANCE

Abstract

This paper presents a systematic bibliometric analysis of applications of the system dynamics (SD) methodology in economics and finance, based on 945 Scopus-indexed publications from 1980-2026. The analytical framework combines frequency distribution analysis, thematic classification by author keywords, citation metrics, and keyword co-occurrence analysis. The results demonstrate consistent growth in SD-related publication activity, from 42 papers in 1980–1999 to 353 in 2020–2026. The thematic structure is dominated by Innovation and Technology (262 papers), Construction and Infrastructure (191), and Sustainability (157), while financial applications such as Banking and Credit (17), Capital Structure (15), and Taxation (30) remain significantly underrepresented. Instrumental analysis reveals VenSim as the dominant simulation platform (44 mentions), with Python-based tools virtually absent from the sample (1 mention). The XMILE interoperability standard is not referenced in any abstract within the sample. A classification matrix maps twelve thematic clusters against methodological characteristics, including primary tools, hybrid approaches, validation reporting, and Python integration. Four research gaps are identified and substantiated quantitatively: the limited application of SD in taxation and fiscal regulation, the absence of Python integration in financial SD research, the lack of a micro-to-macro derivation methodology linking enterprise-level stock-flow models to jurisdictional tax dynamics, and the systemic gap between established SD validation protocols and actual reporting practices. The proposed classification matrix and gap identification provide a quantitative foundation for directing future SD research toward underexplored domains of economic and financial analysis.