{"title":"基于系统动力学模拟的印尼电动摩托车市场补贴政策情景分析","authors":"Roni Zakaria Raung , Wahyudi Sutopo , Muhammad Hisjam , Djoni Hartono","doi":"10.1016/j.trip.2025.101487","DOIUrl":null,"url":null,"abstract":"<div><div>With over 130 million motorcycles, Indonesia faces a critical challenge in transitioning to electric mobility to meet its carbon emission reduction commitments under the Paris Agreement. Despite the existing government incentives and subsidies, the adoption of electric motorcycles (EM) remains critically low, only 0.18% of the 13 million units targeted by 2030. This study aims to evaluate the effectiveness of current EM subsidy and incentive policies and to determine the suitable strategies for achieving the 2030 target. It adapts PTTMAM model, a system dynamics (SD) model that captures the complex interactions among four market agents: users, manufacturers, infrastructure providers, and government, to the context of EM in Indonesia. It also enriches the willingness to consider (WTC) framework within the model by incorporating behavioral variables such as lifestyle and awareness of future trends. The model is calibrated and validated using historical data (2013–2023) through sensitivity and extreme case analysis. A total of 72 subsidy and incentive policy scenarios involving the market agents were constructed to assess the achievement of current policies and identify optimal strategies to reach government’s target. Simulation results of the scenarios reveal that current policies are insufficient, projecting only 15.9% achievement of the 2030 target. More aggressive interventions, including extended subsidies, carbon taxes, and electricity incentives, could enable reaching the target by 2033. Hence, the existing 2030 goal appears overly ambitious without strategic adjustments. This study underscores the need for policy redesign and offers a robust, behaviorally informed SD framework to guide Indonesia’s electric mobility transition.</div></div>","PeriodicalId":36621,"journal":{"name":"Transportation Research Interdisciplinary Perspectives","volume":"32 ","pages":"Article 101487"},"PeriodicalIF":3.9000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scenario analysis of subsidy policies on electric motorcycle market in Indonesia using system dynamics simulation\",\"authors\":\"Roni Zakaria Raung , Wahyudi Sutopo , Muhammad Hisjam , Djoni Hartono\",\"doi\":\"10.1016/j.trip.2025.101487\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With over 130 million motorcycles, Indonesia faces a critical challenge in transitioning to electric mobility to meet its carbon emission reduction commitments under the Paris Agreement. Despite the existing government incentives and subsidies, the adoption of electric motorcycles (EM) remains critically low, only 0.18% of the 13 million units targeted by 2030. This study aims to evaluate the effectiveness of current EM subsidy and incentive policies and to determine the suitable strategies for achieving the 2030 target. It adapts PTTMAM model, a system dynamics (SD) model that captures the complex interactions among four market agents: users, manufacturers, infrastructure providers, and government, to the context of EM in Indonesia. It also enriches the willingness to consider (WTC) framework within the model by incorporating behavioral variables such as lifestyle and awareness of future trends. The model is calibrated and validated using historical data (2013–2023) through sensitivity and extreme case analysis. A total of 72 subsidy and incentive policy scenarios involving the market agents were constructed to assess the achievement of current policies and identify optimal strategies to reach government’s target. Simulation results of the scenarios reveal that current policies are insufficient, projecting only 15.9% achievement of the 2030 target. More aggressive interventions, including extended subsidies, carbon taxes, and electricity incentives, could enable reaching the target by 2033. Hence, the existing 2030 goal appears overly ambitious without strategic adjustments. This study underscores the need for policy redesign and offers a robust, behaviorally informed SD framework to guide Indonesia’s electric mobility transition.</div></div>\",\"PeriodicalId\":36621,\"journal\":{\"name\":\"Transportation Research Interdisciplinary Perspectives\",\"volume\":\"32 \",\"pages\":\"Article 101487\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Interdisciplinary Perspectives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590198225001666\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Interdisciplinary Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590198225001666","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Scenario analysis of subsidy policies on electric motorcycle market in Indonesia using system dynamics simulation
With over 130 million motorcycles, Indonesia faces a critical challenge in transitioning to electric mobility to meet its carbon emission reduction commitments under the Paris Agreement. Despite the existing government incentives and subsidies, the adoption of electric motorcycles (EM) remains critically low, only 0.18% of the 13 million units targeted by 2030. This study aims to evaluate the effectiveness of current EM subsidy and incentive policies and to determine the suitable strategies for achieving the 2030 target. It adapts PTTMAM model, a system dynamics (SD) model that captures the complex interactions among four market agents: users, manufacturers, infrastructure providers, and government, to the context of EM in Indonesia. It also enriches the willingness to consider (WTC) framework within the model by incorporating behavioral variables such as lifestyle and awareness of future trends. The model is calibrated and validated using historical data (2013–2023) through sensitivity and extreme case analysis. A total of 72 subsidy and incentive policy scenarios involving the market agents were constructed to assess the achievement of current policies and identify optimal strategies to reach government’s target. Simulation results of the scenarios reveal that current policies are insufficient, projecting only 15.9% achievement of the 2030 target. More aggressive interventions, including extended subsidies, carbon taxes, and electricity incentives, could enable reaching the target by 2033. Hence, the existing 2030 goal appears overly ambitious without strategic adjustments. This study underscores the need for policy redesign and offers a robust, behaviorally informed SD framework to guide Indonesia’s electric mobility transition.