System Dynamics Modelling of the Indonesian Compressed Natural Gas (CNG) Supply Chain: Analysis of CNG Refuelling Station Utilization and Sectoral Allocation Policies on Supply–Demand Balance (2013–2040)

ABSTRACT This study analyses the dynamics of the compressed natural gas (CNG) supply chain in Indonesia using a system dynamics approach, focusing on the role of CNG refuelling station (SPBG) utilization and sectoral allocation policies in influencing supply–demand balance and system performance. The simulation model was developed based on historical data from 2013 to 2023 and projected up to 2040 to evaluate various policy scenarios. The results show that increasing SPBG utilization can significantly enhance distribution capacity and revenue, but it also accelerates demand growth, which creates pressure on the supply side if not balanced by strengthened upstream capacity. Sectoral allocation policies are shown to accelerate the system's economic growth but have the potential to create supply deficits if not aligned with domestic production capacity. These findings indicate the existence of systemic trade‐offs and a limits‐to‐growth pattern in CNG management. This study contributes by integrating infrastructure utilization, policy interventions, and supply constraints within a single dynamic framework. Practically, the findings emphasize the importance of upstream–downstream policy coordination based on simulation analysis to support sustainable energy management.

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Publication Details

Journal
Systems Research and Behavioral Science
Published
2026-08-18
DOI
https://doi.org/10.1002/sres.70136
Primary Topic
Global Energy Security and Policy
Type
article
Field-Weighted Citation Impact
0.00
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article

System Dynamics Modelling of the Indonesian Compressed Natural Gas (CNG) Supply Chain: Analysis of CNG Refuelling Station Utilization and Sectoral Allocation Policies on Supply–Demand Balance (2013–2040)

Fadrian Dwiki Maulanda, Dliyaa Ul Haq, Dinda Thalia
Systems Research and Behavioral Science
Global Energy Security and Policy
article

System Dynamics Modelling of the Indonesian Compressed Natural Gas (CNG) Supply Chain: Analysis of CNG Refuelling Station Utilization and Sectoral Allocation Policies on Supply–Demand Balance (2013–2040)

Fadrian Dwiki Maulanda, Dliyaa Ul Haq, Dinda Thalia
article en

Abstract

ABSTRACT This study analyses the dynamics of the compressed natural gas (CNG) supply chain in Indonesia using a system dynamics approach, focusing on the role of CNG refuelling station (SPBG) utilization and sectoral allocation policies in influencing supply–demand balance and system performance. The simulation model was developed based on historical data from 2013 to 2023 and projected up to 2040 to evaluate various policy scenarios. The results show that increasing SPBG utilization can significantly enhance distribution capacity and revenue, but it also accelerates demand growth, which creates pressure on the supply side if not balanced by strengthened upstream capacity. Sectoral allocation policies are shown to accelerate the system's economic growth but have the potential to create supply deficits if not aligned with domestic production capacity. These findings indicate the existence of systemic trade‐offs and a limits‐to‐growth pattern in CNG management. This study contributes by integrating infrastructure utilization, policy interventions, and supply constraints within a single dynamic framework. Practically, the findings emphasize the importance of upstream–downstream policy coordination based on simulation analysis to support sustainable energy management.

Systems Research and Behavioral Science
Bandung Institute of Technology (ID), University of Brawijaya (ID)
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Global Energy Security and Policy
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System Dynamics Modelling of the Indonesian Compressed Natural Gas (CNG) Supply Chain: Analysis of CNG Refuelling Station Utilization and Sectoral Allocation Policies on Supply–Demand Balance (2013–2040) — Fadrian Dwiki Maulanda, Dliyaa Ul Haq, et al. · Systems Research and Behavioral Science (2026) | TGRS Research Map | TGRS