System dynamics model of refuse-derived fuel adoption in Indonesia's cement industry: model file and simulation dataset

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System dynamics model of refuse-derived fuel adoption in
Indonesia's cement industry: model file and simulation dataset
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ASSOCIATED ARTICLE
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Ummatin KK, Hidayatno A, Setiawan AD, Abubakar MAS.
Readiness-Contingent Policy Design for Refuse-Derived Fuel Adoption in
Indonesia's Cement Industry: A Scenario-Based System Dynamics Analysis.
Submitted to Clean Technologies and Environmental Policy (Springer).
[Article DOI to be added on publication]

Corresponding author: Akhmad Hidayatno
Systems Engineering, Modeling and Simulation Laboratory,
Department of Industrial Engineering, Faculty of Engineering,
Universitas Indonesia, Depok, Indonesia
E-mail: akhmad.hidayatno@ui.ac.id

CONTENTS
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RDF_adoption_model.mdl
    Vensim model file, plain-text format. Six modules: population,
    MSW generation, RDF adoption, RDF production, RDF demand, and
    avoided CO2 emissions. Readable in any text editor.

RDF_adoption_model.2mdl
    Same model, Vensim binary format.

run_baseline.vdfx
    Simulation run output (Vensim binary dataset format).

annual_simulation_outputs.xlsx
    Annual simulation outputs, 2026-2045, for every condition and
    instrument combination reported in the article. Sheets:
      README                - run settings and units
      Baseline_by_condition - no-policy baseline, three conditions
      Low Readiness         - four instruments
      Circular Transition   - four instruments
      Enabling Ecosystem    - four instruments
      Validation            - behaviour-reproduction test data
      Cumulative_summary    - cumulative RDF and avoided CO2

Supplementary_Information_FIX.docx
    Supplementary Information accompanying the article. Contains the
    stock-and-flow structure of each of the six modules (Figs. S1-S6)
    and the complete model formulation (Tables S1-S6): every variable,
    its dimension, unit, and defining equation, including the values of
    all model constants.

NOTE ON PARAMETERS
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All parameter values used in the simulations are given in two places:
Tables S1-S6 of the Supplementary Information, and the model file
itself, which is plain text and lists every constant and lookup
function. No separate parameter spreadsheet is required to reproduce
the results.

MODEL SETTINGS
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Software        Vensim (PLE or higher; the .mdl file opens in any version)
Initial time    2020
Final time      2045
Time step       0.25 year
Integration     Euler
Spatial scope   East Java province, Indonesia

HOW TO REPRODUCE
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1. Open RDF_adoption_model.mdl in Vensim.
2. Set the readiness condition by applying the per-capita waste
   generation, RDF yield, and coal price ranges given in Table 2 of the
   article.
3. Apply an instrument: tipping fee Rp100,000/t or Rp200,000/t, or the
   TSR target trajectory rising from 10% to 50% over 2025-2045.
4. Run to 2045. Outputs should match annual_simulation_outputs.xlsx.

Figures 5 to 8 of the article are generated directly from
annual_simulation_outputs.xlsx.

NOTES AND LIMITATIONS
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- Avoided-emission factors are held constant in the model
  (1.96 t CO2/t RDF landfill methane; 2.0 t CO2/t RDF coal displacement).
  Emission results are therefore structural model outputs, not
  empirically calibrated values, and await independent life-cycle
  validation.
- RDF yield is an exogenous scenario condition, not an endogenous
  variable.
- The model represents East Java and is not calibrated to other
  Indonesian provinces.

COPYRIGHT AND LICENCE
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(c) 2026 The Authors (K.K. Ummatin, A. Hidayatno, A.D. Setiawan,
M.A.S. Abubakar). Made available under CC BY 4.0.

Data and documentation:  CC BY 4.0
Model file:              CC BY 4.0

You are free to share and adapt this material for any purpose, provided
appropriate credit is given to the authors and to the associated article.

CITATION
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Ummatin KK, Hidayatno A, Setiawan AD, Abubakar MAS (2026)
System dynamics model of refuse-derived fuel adoption in Indonesia's
cement industry: model file and simulation dataset [Data set].
Zenodo. https://doi.org/10.5281/zenodo.21866680