IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2023-06-13.html
   My bibliography  Save this article

Gasoline Policy Simulation to Increase Responsiveness Using System Dynamics: A Case Study of Indonesia’s Gasoline Downstream Supply Chain

Author

Listed:
  • Sylvia Mardiana

    (Faculty of Administrative Science, Universitas Indonesia, Indonesia.)

Abstract

In the supply chain, inventory planning plays a crucial role in achieving a balance between supply and demand. This study aims to investigate a supply chain policy that can achieve an impressive level of responsiveness, reaching close to 100%. Additionally, by focusing on the supply chain of RON 92 gasoline in Indonesia, the research aims to identify the key factors influencing responsiveness instability. To achieve these objectives, a simulation model was used to analyze the inventory policy, considering various factors such as demand, production, safety stock coverage, transportation delays, production capacity, and importation due to insufficient production capacity. The results showed that forecasting accuracy is the main determinant of the responsiveness rate. Moreover, maintaining a minimum inventory level of 28 days yielded an impressive 99% responsiveness rate, provided that the deviation in demand does not exceed 5% of the forecast. The analytical tool used in the system dynamics framework was a simulation, which significantly contributed to the research findings. However, it is important to note that this research has limitations, specifically in its inability to analyze crude oil supply. Therefore, further research is necessary to thoroughly examine this aspect and gain a more comprehensive understanding of the overall supply chain dynamics.

Suggested Citation

  • Sylvia Mardiana, 2023. "Gasoline Policy Simulation to Increase Responsiveness Using System Dynamics: A Case Study of Indonesia’s Gasoline Downstream Supply Chain," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 109-118, November.
    • Handle: RePEc:eco:journ2:2023-06-13
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/14933/7549
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/14933
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rendon-Sagardi, Miguel A. & Sanchez-Ramirez, Cuauhtemoc & Cortes-Robles, Guillermo & Alor-Hernandez, Giner & Cedillo-Campos, Miguel G., 2014. "Dynamic analysis of feasibility in ethanol supply chain for biofuel production in Mexico," Applied Energy, Elsevier, vol. 123(C), pages 358-367.
    2. Ansari, Nastaran & Seifi, Abbas, 2013. "A system dynamics model for analyzing energy consumption and CO2 emission in Iranian cement industry under various production and export scenarios," Energy Policy, Elsevier, vol. 58(C), pages 75-89.
    3. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    4. Fitriyanti Mayasari & Rinaldy Dalimi & Widodo Wahyu Purwanto, 2019. "Projection of Biodiesel Production in Indonesia to Achieve National Mandatory Blending in 2025 using System Dynamics Modeling," International Journal of Energy Economics and Policy, Econjournals, vol. 9(6), pages 421-429.
    5. Rose, Adam & Wei, Dan & Paul, Donald, 2018. "Economic consequences of and resilience to a disruption of petroleum trade: The role of seaports in U.S. energy security," Energy Policy, Elsevier, vol. 115(C), pages 584-615.
    6. Kristianto, Yohanes & Gunasekaran, Angappa & Helo, Petri, 2017. "Building the “Triple R” in global manufacturing," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 607-619.
    7. Pan, Lingying & Liu, Pei & Li, Zheng, 2017. "A system dynamic analysis of China’s oil supply chain: Over-capacity and energy security issues," Applied Energy, Elsevier, vol. 188(C), pages 508-520.
    8. Sylvia Mardiana & Ferdinand Saragih & Martani Huseini, 2020. "Forecasting Gasoline Demand in Indonesia Using Time Series," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 132-145.
    9. Kourentzes, Nikolaos & Trapero, Juan R. & Barrow, Devon K., 2020. "Optimising forecasting models for inventory planning," International Journal of Production Economics, Elsevier, vol. 225(C).
    10. Moradi Nasab, N. & Amin-Naseri, M.R., 2016. "Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain," Energy, Elsevier, vol. 114(C), pages 708-733.
    11. Poles, Roberto, 2013. "System Dynamics modelling of a production and inventory system for remanufacturing to evaluate system improvement strategies," International Journal of Production Economics, Elsevier, vol. 144(1), pages 189-199.
    12. Soroush Saghafian & Brian Tomlin, 2016. "The Newsvendor under Demand Ambiguity: Combining Data with Moment and Tail Information," Operations Research, INFORMS, vol. 64(1), pages 167-185, February.
    13. Ryu, Kwangyeol & Moon, Ilkyeong & Oh, Seungjin & Jung, Mooyoung, 2013. "A fractal echelon approach for inventory management in supply chain networks," International Journal of Production Economics, Elsevier, vol. 143(2), pages 316-326.
    14. Kumar, Sourabh & Kumar Barua, Mukesh, 2022. "Modeling and investigating the interaction among risk factors of the sustainable petroleum supply chain," Resources Policy, Elsevier, vol. 79(C).
    15. Chen, Sai & Ding, Yueting & Song, Yan & Zhang, Ming & Nie, Rui, 2023. "Study on China's energy system resilience under the scenarios of long-term shortage of imported oil," Energy, Elsevier, vol. 270(C).
    16. Ashutosh Sheel & Y.P. Singh & Vishnu Nath, 2020. "Managing agility in the downstream petroleum supply chain," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 20(2), pages 269-294.
    17. Becerra-Fernandez, Mauricio & Cosenz, Federico & Dyner, Isaac, 2020. "Modeling the natural gas supply chain for sustainable growth policy," Energy, Elsevier, vol. 205(C).
    18. Kazemi, Yasaman & Szmerekovsky, Joseph, 2015. "Modeling downstream petroleum supply chain: The importance of multi-mode transportation to strategic planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 111-125.
    19. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    20. Marcus Brandenburg & Tim Gruchmann & Nelly Oelze, 2019. "Sustainable Supply Chain Management—A Conceptual Framework and Future Research Perspectives," Sustainability, MDPI, vol. 11(24), pages 1-15, December.
    21. Cannella, Salvatore & Dominguez, Roberto & Ponte, Borja & Framinan, Jose M., 2018. "Capacity restrictions and supply chain performance: Modelling and analysing load-dependent lead times," International Journal of Production Economics, Elsevier, vol. 204(C), pages 264-277.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dehghan, Hamed & Amin-Naseri, Mohammad Reza & Nahavandi, Nasim, 2021. "A system dynamics model to analyze future electricity supply and demand in Iran under alternative pricing policies," Utilities Policy, Elsevier, vol. 69(C).
    2. Farahani, Mohsen & Rahmani, Donya, 2017. "Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap," Energy, Elsevier, vol. 141(C), pages 991-1003.
    3. Becerra-Fernandez, Mauricio & Sarmiento, Alfonso T. & Cardenas, Laura M., 2023. "Sustainability assessment of the solar energy supply chain in Colombia," Energy, Elsevier, vol. 282(C).
    4. Carmona-Benítez, Rafael Bernardo & Cruz, Héctor, 2023. "A multiproduct gasoline supply chain with product standardization and postponement strategy," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    5. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    6. Pudasaini, Pramesh, 2021. "Integrated planning of downstream petroleum supply chain: a multi-objective stochastic approach," Operations Research Perspectives, Elsevier, vol. 8(C).
    7. Rostami-Tabar, Bahman & Ali, Mohammad M. & Hong, Tao & Hyndman, Rob J. & Porter, Michael D. & Syntetos, Aris, 2022. "Forecasting for social good," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1245-1257.
    8. Gurbanov, Sarvar, 2021. "Role of Natural Gas Consumption in the Reduction of CO₂ Emissions: Case of Azerbaijan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14(22).
    9. Sujan Piya & Ahm Shamsuzzoha & Mohammad Khadem & Nasr Al-Hinai, 2020. "Identification of Critical Factors and Their Interrelationships to Design Agile Supply Chain: Special Focus to Oil and Gas Industries," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 263-281, September.
    10. Kourentzes, Nikolaos & Athanasopoulos, George, 2021. "Elucidate structure in intermittent demand series," European Journal of Operational Research, Elsevier, vol. 288(1), pages 141-152.
    11. Spiliotis, Evangelos & Makridakis, Spyros & Kaltsounis, Anastasios & Assimakopoulos, Vassilios, 2021. "Product sales probabilistic forecasting: An empirical evaluation using the M5 competition data," International Journal of Production Economics, Elsevier, vol. 240(C).
    12. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    13. Hannan Amoozad Mahdiraji & Aliasghar Abbasi Kamardi & Moein Beheshti & Seyed Hossein Razavi Hajiagha & Luis Rocha-Lona, 2022. "Analysing supply chain coordination mechanisms dealing with repurposing challenges during Covid-19 pandemic in an emerging economy: a multi-layer decision making approach," Operations Management Research, Springer, vol. 15(3), pages 1341-1360, December.
    14. Taleizadeh, Ata Allah & Shokr, Iman & Konstantaras, Ioannis & VafaeiNejad, Mahyar, 2020. "Stock replenishment policies for a vendor-managed inventory in a retailing system," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    15. Straubert, Christian, 2024. "A continuous approximation location-inventory model with exact inventory costs and nonlinear delivery lead time penalties," International Journal of Production Economics, Elsevier, vol. 268(C).
    16. Ravago, Majah-Leah V. & Fabella, Raul V. & Jandoc, Karl Robert L. & Frias, Renzi G. & Magadia, J. Kathleen P., 2021. "Gauging the market potential for natural gas among Philippine manufacturing firms," Energy, Elsevier, vol. 237(C).
    17. Boylan, John E. & Babai, M. Zied, 2022. "Estimating the cumulative distribution function of lead-time demand using bootstrapping with and without replacement," International Journal of Production Economics, Elsevier, vol. 252(C).
    18. Sudip Adak & G. S. Mahapatra, 2021. "Effect of inspection and rework of probabilistic defective production on two-layer supply chain incorporating deterioration and reliability dependent demand," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 565-578, June.
    19. Stavros Sindakis & Saloome Showkat & Jiafu Su, 2023. "Unveiling the Influence: Exploring the Impact of Interrelationships among E-Commerce Supply Chain Members on Supply Chain Sustainability," Sustainability, MDPI, vol. 15(24), pages 1-27, December.
    20. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.

    More about this item

    Keywords

    Policy Simulation; Inventory; Responsiveness; System Dynamics; Petroleum Supply Chain;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2023-06-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.