Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/230680
Title: LEARNING-BY-DOING IN SINGAPORE’S TAXI MARKET
Authors: WANG SHUXIAO
ORCID iD:   orcid.org/0000-0002-4321-475X
Keywords: Learning-by-doing, taxi industry, the Dirichlet learning, market knowledge, feedback-seeking
Issue Date: 7-Apr-2022
Citation: WANG SHUXIAO (2022-04-07). LEARNING-BY-DOING IN SINGAPORE’S TAXI MARKET. ScholarBank@NUS Repository.
Abstract: We study taxi drivers’ location choices in Singapore’s taxi market. Using a unique dataset consisting of taxi drivers’ trip records and GPS trajectories, we estimate a dynamic discrete choice model with a Dirichlet learning framework incorporated, in which taxi drivers choose where to search for passengers when they are vacant and update their belief regarding the demand condition by accumulating multiple types of experiences. Our results demonstrate that the experience of finding street-hail trips is the most impactful one in updating the probability of finding passengers, followed by the experience of finding booking trips and not finding trips. We further document that the effect sizes of the different types of experiences are affected by (1) the extent of gain or loss of the corresponding experience, (2) the rarity of the corresponding experience, and (3) the amount of the same type of experience accumulated in history.
URI: https://scholarbank.nus.edu.sg/handle/10635/230680
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
WangS.pdf1.04 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

31
checked on Dec 1, 2022

Download(s)

4
checked on Dec 1, 2022

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.