Multimodal Transportation Policy to Address The High Cost of Goods in 3T Regions (Lagging, Frontier, and Outer): Bibliometric Analysis and Future Research Agenda (Case Study of Papua)

Authors

  • Nikolas Makanuay Politeknik Penerbangan Jayapura, Indonesia
  • Rifqi Raza Bunahri Politeknik Penerbangan Jayapura, Indonesia
  • Musri Kona Politeknik Penerbangan Jayapura, Indonesia
  • Dhian Supardam Politeknik Penerbangan Indonesia Curug, Indonesia
  • Hadi Prayitno Akademi Penerbang Indonesia Banyuwangi, Indonesia

DOI:

https://doi.org/10.31933/dijemss.v5i1.2115

Keywords:

3T region, commodity prices, multimodal transportation, papua, transportation policies

Abstract

This study discusses the implementation of multimodal transportation policies in Papua, as an effort to address the high cost of goods in the region with the aim of reducing logistics costs and accelerating economic growth. Shipping rates in Indonesia remain an unresolved issue, especially in the Papua region, classified as a 3T area (lagging, frontier, and outer), leading to high commodity prices. The research employs bibliometric analysis using the Scopus database as its data source. Out of a total of 5,930 articles found, a filtering process considering location, keywords, and a time range from 2009 to 2023 was conducted. As a result, 200 relevant articles were identified for analysis, and from this pool, 15 articles most aligned with relevant keywords were selected as the primary references for this study. The research findings indicate that the implementation of multimodal transportation policies in Papua has successfully reduced price disparities and improved accessibility to mountainous regions. However, challenges persist in the development of multimodal transportation in 3T areas, prompting recommendations for policies such as collaboration and logistics integration across modes, seaplane transportation, and mountain flying training to optimize logistics delivery in mountainous areas. Additionally, the use of unmanned aerial vehicles (drones) for more efficient logistics delivery is suggested. Furthermore, future research should focus on various aspects of multimodal transportation, including ride-sharing, mobility as a service, railway transportation, traffic congestion, land use, climate change, greenhouse gas emissions, traffic control, transportation costs, safety, travel time, social welfare, and expenses. This study provides insights into the positive impact of multimodal transportation policies in Papua and offers guidance for future development to address the issue of high commodity prices in 3T regions.

References

Azka, R. M. (2020). 5 Tahun Beroperasi, Tol Laut Baru Berhasil Distribusi Secara Multimoda! Bisnis.Com, 1. https://ekonomi.bisnis.com/read/20201224/98/1335028/5-tahun-beroperasi-tol-laut-baru-berhasil-distribusi-secara-multimoda
Bahtiar, Adjisasmita, S. A., Ramli, M. I., & Pasra, M. (2020). Model influence means operational performance on the port of Jayapura. IOP Conference Series: Earth and Environmental Science, 419(1), 012097. https://doi.org/10.1088/1755-1315/419/1/012097
Buchari, E. (2009). A multimodal public transport planning guidance for sustainable transport in developing countries. International Journal of Environment and Sustainable Development, 8(3–4), 263–285. https://doi.org/10.1504/ijesd.2009.024631
Buchari, E. (2015). Transportation demand management: A park and ride system to reduce congestion in Palembang city Indonesia. In A. null, M. I., & H. D. (Eds.), Procedia Engineering (Vol. 125, pp. 512–518). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2015.11.047
Bunahri, R. R. (2023). Factors Influencing Air Cargo Business?: Business Plan and Strategy , Professional Human Resources , and Airlines ’ Performance. Journal of Accounting and Finance Management, 4(2), 220–226. https://doi.org/https://doi.org/10.38035/jafm.v4i2.220
Bunahri, R. R., Supardam, D., Prayitno, H., & Kuntadi, C. (2023). Determination of Air Cargo Performance: Analysis of Revenue Management, Terminal Operations, and Aircraft Loading (Air Cargo Management Literature Review). Dinasti International Journal of Management Science, 4(5), 833–844. https://doi.org/10.31933/dijms.v4i5
Hadjidemetriou, G. M., Teal, J., Kapetas, L., & Parlikad, A. K. (2022). Flexible Planning for Intercity Multimodal Transport Infrastructure. Journal of Infrastructure Systems, 28(1). https://doi.org/10.1061/(ASCE)IS.1943-555X.0000664
Han, B., Wan, M., Zhou, Y., & Su, Y. (2020). Evaluation of Multimodal Transport in China Based on Hesitation Fuzzy Multiattribute Decision-Making. Mathematical Problems in Engineering, 2020, 1–9. https://doi.org/10.1155/2020/1823068
Indriastiwi, F., & Hadiwardoyo, S. P. (2023). The Integrated Strategic Planning of Multimodal Freight Transport Network Under Infrastructure Budget Limitation. International Journal of Transport Development and Integration, 7(1), 1–11. https://doi.org/10.18280/ijtdi.070101
Kasim, A. M. R., Wicaksono, A. D., & Kurniawan, E. B. (2017). The integration level of public transportation in Makassar City. IOP Conference Series: Earth and Environmental Science, 70, 012021. https://doi.org/10.1088/1755-1315/70/1/012021
Li, X., Zhou, R., & Zhu, L. (2022). Multi-modal Transport International Experience and Reference to China. In L. Z. & S. J. (Eds.), Chinese Control Conference, CCC (Vols. 2022-July, pp. 7526–7531). IEEE Computer Society. https://doi.org/10.23919/CCC55666.2022.9902362
logisticknews. (2021, April 27). Kemenhub Buka Konektivitas Multimoda di Nduga Papua. Logiscticknews, 1. https://www.logistiknews.id/2021/04/27/kemenhub-buka-konektivitas-multimoda-di-nduga-papua/
Mokhtar, H., Redi, A. A. N. P., Krishnamoorthy, M., & Ernst, A. T. (2019). An intermodal hub location problem for container distribution in Indonesia. Computers & Operations Research, 104, 415–432. https://doi.org/10.1016/j.cor.2018.08.012
Oh, S., Seshadri, R., Azevedo, C. L., Kumar, N., Basak, K., & Ben-Akiva, M. (2020). Assessing the impacts of automated mobility-on-demand through agent-based simulation: A study of Singapore. Transportation Research Part A: Policy and Practice, 138, 367–388. https://doi.org/10.1016/j.tra.2020.06.004
PSP. (2023). Sejumlah Komoditas di Pasar Wamanggu Alami Penurunan Harga. PSP.Com, 1. https://papuaselatanpos.com/2023/07/24/sejumlah-komoditas-di-pasar-wamanggu-alami-penurunan-harga/
Sandria, F. (2023). Melonjak 30,4%, Freeport Indonesia (PTFI) Knatongi Laba Bersih US$ 3,3 Miliar di 2022. BUSINESSINSIGHT, 1. https://insight.kontan.co.id/news/melonjak-304-freeport-indonesia-ptfi-kantongi-laba-bersih-us-33-miliar-di-2022
Yang, Z., Xin, X., Chen, K., & Yang, A. (2021). Coastal container multimodal transportation system shipping network design—toll policy joint optimization model. Journal of Cleaner Production, 279. https://doi.org/10.1016/j.jclepro.2020.123340
Zhang, X., Yuan, X., & Jiang, Y. (2021). Optimization of multimodal transportation under uncertain demand and stochastic carbon trading price. Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 41(10), 2609–2620. https://doi.org/10.12011/SETP2020-0231

Published

2023-11-26

How to Cite

Nikolas Makanuay, Rifqi Raza Bunahri, Musri Kona, Dhian Supardam, & Hadi Prayitno. (2023). Multimodal Transportation Policy to Address The High Cost of Goods in 3T Regions (Lagging, Frontier, and Outer): Bibliometric Analysis and Future Research Agenda (Case Study of Papua). Dinasti International Journal of Education Management And Social Science, 5(1), 34–42. https://doi.org/10.31933/dijemss.v5i1.2115