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MRT as Climate Policy in Urban Transportation

  • Siti MaimunahEmail author
  • Shinji Kaneko
Chapter

Abstract

Since the transportation sector is one of the main contributors of GHG emissions in Indonesia, having a clear direction of climate policy is very important. Developing mass rapid transit (MRT) as the climate policy in urban transportation is urgently needed since it can encourage people to use public transport. However, some policies seem conflicting, either encouraging or discouraging people to use public transport. Therefore, balancing conflicting policies is important. Fuel subsidy is such policy that hampers potential impacts of the MRT being currently under construction in one of the most congested cities in the world, Jakarta. Describing the current transport policies in Jakarta as well as the current commuters’ behavior on transport mode choices is a basis to deliver the appropriate policies. Repeated choice experiments for private vehicle commuters in Jakarta on preferences if they would be willing to shift to MRT once it becomes available have been conducted before and after the removal of the fuel subsidy. The mixed logit models revealed that the scale of impacts on probability to shift for MRT due to subsidy removal is significant compared to the best available feasible options for MRT service improvements. Moreover, after the actual implementation of the fuel subsidy removal, more motorcycle commuters are willing to shift compared to the hypothetical scenario of the fuel subsidy removal. Shifting from using cars or motorcycles to MRT also can reduce the CO2 emission. Under the assumptions that MRT will be operated by electric-based systems and the CO2 emission is negligible, the shifting of commuters from cars and motorcycles can reduce the CO2 emission by 10.52 % per year, using the year 2013 as the base year. Moreover, because of the fuel subsidy removal, the reduction of CO2 emission will be higher, up to 13.28 % per year.

Keywords

MRT Climate policy CO2 emission reduction Logit model Mixed policy scenarios 

References

  1. BAPPENAS, JICA (2004) The study on integrated transportation master plan for Jabodetabek (Phase 2)Google Scholar
  2. Ben-Akiva M, De Palma A, Isam K (1991) Dynamic network models and driver information systems. Transp Res A Gen 25(5):251–266CrossRefGoogle Scholar
  3. Cullinane S (1992) Attitudes towards the car in the U.K. Some implications for policies on congestion and the environment. Transp Res A 26A(4):291–301Google Scholar
  4. Cullinane S, Cullinane K (2003) Car dependence in a public transport dominated city: evidence from Hong Kong. Transp Res Part D: Transp Environ 8(2):129–138CrossRefGoogle Scholar
  5. Cunningham WP, Cunningham MA (2010) Environmental science a global concern, vol 11. Mc Graw Hill Companies, DubuqueGoogle Scholar
  6. Deng T, Nelson JD (2013) Bus rapid transit implementation in Beijing: an evaluation of performance and impacts. Res Transp Econ 39(1):108–113CrossRefGoogle Scholar
  7. Ellaway A, Macintyre S, Hiscock R, Kearns A (2003) In the driving seat: psychosocial benefits from private motor vehicle transport compared to public transport. Transport Res F: Traffic Psychol Behav 6(3):217–231CrossRefGoogle Scholar
  8. Environmental Management Agency of Jakarta Province (2013) Status Lingkungan Hidup Daerah Provinsi Daerah Khusus Ibukota Jakarta Tahun 2013Google Scholar
  9. Hiscock R, Macintyre S, Kearns A, Ellaway A (2002) Means of transport and ontological security: do cars provide psycho-social bene ® ts to their users? Transp Res D 7:119–135CrossRefGoogle Scholar
  10. Ministry of Economic Affairs, Japan International Cooperation Agency (2012) JABODETABEK urban transportation policy integration project in the Republic IndonesiaGoogle Scholar
  11. Ministry of Energy and Mineral Resources (2014) Handbook of energy and economic statistics of Indonesia 2013Google Scholar
  12. MRT Jakarta (2013a) MRT Jakarta project. Retrieved from www.jakartamrt.com
  13. MRT Jakarta (2013b) MRT overview. Retrieved from http://www.jakartamrt.com/
  14. Noland RB, Small K a, Koskenoja PM, Chu X (1998) Simulating travel reliability. Reg Sci Urban Econ 28(5):535–564CrossRefGoogle Scholar
  15. Rotaris L, Danielis R (2014) The impact of transportation demand management policies on commuting to college facilities: a case study at the University of Trieste, Italy. Transp Res A Policy Pract 67:127–140CrossRefGoogle Scholar
  16. Statistics of Jakarta Province (2014) Statistik Daerah Provinsi DKI JakartaGoogle Scholar
  17. Suryo R, Fan C, Weiler S (2007) Commuting choices and congestion taxes in industrializing Indonesia. Soc Sci J 44(2):253–273CrossRefGoogle Scholar

Copyright information

© Springer Japan 2016

Authors and Affiliations

  1. 1.Research and Development UnitMinistry of Transportation of Republic of IndonesiaJakartaIndonesia
  2. 2.Graduate School for International Development and CooperationHiroshima UniversityHiroshimaJapan

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