Page 50 - Proceeding of Atrans Young Researcher's Forum 2019_Neat

“Transportation for A Better Life:
Smart Mobility for Now and Then”

23 August 2019, Bangkok, Thailand

Table 5 Travel mode choice model mode choice among K-12 school students is to
reduce travel distance from home to school less than
Parameters Transport mode MNL
1 km by constructing more state schools or
Intercept Public -3.054 (0.292)*** motivating the private sector to invest in building
Private -12.522 (0.911)*** more private schools. The empirical findings are
Household income Public 0.075 (0.02)*** expected to aid policymakers to design proactive
Private 0.206 (0.032)*** planning and policy to encourage non-motorized
mode choice among K-12 school students.
Distance to school Public 2.682 (0.192)***
This is just the preliminary study of the travel mode
Private 2.794 (0.2)***
choice among K-12 students in Metro Manila, and
No. of passengers Public -0.131 (0.118) further research effort is required to develop the
Private 2.372 (0.278)*** travel mode choice models using various discrete
McFadden R 2 0.41 choice algorithms and apply the models to predict
Log-likelihood -613.56 percentage changes with response to changes in the
* significant at the 5% level,
** significant at the 1% level, independent variables.
*** significant at the 0.1% level
The non-motorized mode was used as the reference category. Acknowledgements
The outcomes of this research paper are
funded by a) the Japan International Cooperation
4. Conclusions and Recommendations Agency (JICA) under AUN/SEED-Net project for a
This study intends to explore the Ph.D. Sandwich program at De La Salle University,
determinants (i.e., urban form attributes and Philippines, and Osaka University, Japan; b) the
socioeconomic characteristics) of travel mode Commission on Higher Education Development for
choice (i.e., non-motorized, public, and private) a Project of Development and Application of
among K-12 students in Metro Manila. The Person Transport Desirability Index for the Assessment and
product moment correlation coefficient was used to Planning of Transport Systems in the Philippines;
capture the correlation of the independent variables and c) the Big Data Analytics and Applications
with the dependent variables. Household income, a (MTNN:BDAA) project of the Department of
number of commuters, and commuting distance Science and Technology (DOST), Philippines.
from home to school were found to have moderate
correlations with the dependent variables. After that, References
the probability of travel mode choice conditional on
the three mentioned independent variables was
carried out. It highlighted that students with a lower [1] Trading Economics, "Philippines GDP annual
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[Online].
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[2] Numbeo, "Traffic Index 2018 Mid-Year,"
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[3] ALMEC, "Roadmap for transport for
higher than PHP 40,000 was higher than that infrastructure development for Metro Manila and
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(NEDA)," 2014.
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