Discrete choice modeling for the proposed canal boat transit in western Bangkok, Thailand
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Ampol Karoonsoontawong, Arkar Than Win, Hansa Srilertchaipanij, Kanjanee Budthimedhe , Vasin Kiattikomol, Tassana Boonyoo, Vatanavongs Ratanavaraha, Chai Jaturapitakkul
ผู้เผยแพร่: Elsevier
ปีที่เผยแพร่ (ค.ศ.): 2026
วารสาร: Case Studies on Transport Policy (2213-624X)
นอก: 2213-624X
eISSN: 2213-6258
URL: https://www.sciencedirect.com/science/article/pii/S2213624X26000295
บทคัดย่อ
The proposed canal boat transit (CBT) system, designed to connect metro rail and bus services in western Bangkok, was initiated by an academic institution in collaboration with local communities and stakeholders from both the public and private sectors. The initiative aims to support decarbonization efforts and promote sustainable urban mobility. A stated choice experiment explicitly incorporating the waterborne mode was conducted, and a transport mode choice model was estimated using sampling weights on combined revealed and stated preference (RP and SP) survey data through the nested logit trick. The results reveal that, for the proposed CBT mode, the value of time is highest for first-mile travel time (FMTT) at 22.36 (100.82) baht/hour, followed by wait time (WT) at 19.49 (42.79) baht/hour, and in-vehicle travel time (IVTT) at 1.76 (6.79) baht/hour for the low-income (high-income) group. Mode share comparisons before and after the introduction of CBT indicate slight declines across all existing modes, ranging from 0.02% to 0.04%. The estimated elasticities suggest that a 1% reduction in total cost (TC), FMTT, WT, and IVTT would increase CBT demand by 1.9670%, 0.8249%, 0.3173%, and 0.1269%, respectively. A 1% decrease in any CBT attribute would reduce public transit use more than private vehicle use. Simulations were performed to estimate mode share variations across income groups under different levels of CBT attribute reductions. Targeted incentives may integrate fare reductions to enhance affordability, connectivity improvements to improve accessibility, and community-based support programs to attract both lower- and higher-income users and reduce private car dependence.
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