Simulation of Banking Loan Barriers to Industry: Insights from a System Dynamics Model
Year: 2025
Type: article
Abstract: Industrial financing is pivotal to economic development, yet it faces persistent barriers, including institutional rigidities, informational asymmetries, and macroeconomic volatility, which constrain credit flows and exacerbate underinvestment. This study applies system dynamics modeling to unravel these intricate interactions, constructing a validated framework that delineates causal interdependencies and projects policy outcomes over a 60-month horizon. A comprehensive literature review identified 54 categorized barriers, refined through expert consultations via purposive snowball sampling and causal loop diagramming. A Vensim PLE-based stock and flow model, incorporating six core stocks, was developed and rigorously validated for structural and behavioral accuracy to ensure empirical robustness. Scenario analyses contrasted a baseline with three policy interventions: credit facilitation with institutional reforms, regulatory tightening amid financial stress, and adaptive responses to external shocks (e.g., sanctions). Under the baseline, the system achieved natural equilibrium with gradual growth, moderate bank profitability, and constrained industrial capacity. The “Credit Facilitation and Institutional Improvement” scenario yielded optimal results, with enhanced repayment flexibility and refined credit assessment driving substantial loan growth, elevated profitability, and controlled default risk. Conversely, “Financial Pressure and Regulatory Tightening” induced severe credit contraction, rising non-performing loans, and diminished profitability, underscoring the perils of overly restrictive policies. The “External Shock and Adaptive Response” scenario triggered temporary declines in profitability and credit access, but endogenous mechanisms facilitated partial recovery. These findings affirm that facilitative and institutional policies maximize efficiency and sustainability for the banking and industrial sectors
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7102826217
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