Estimating the Modal Split Ratios of Square Visitors in the Case of Istanbul’s Historical Peninsula: Evidence from Multinominal Logistic Regression Model
Publication: Journal of Urban Planning and Development
Volume 148, Issue 4
Abstract
The continuity of urban activities is provided by a well-oriented transportation network, making sustainable transportation systems a prominent component of sustainable urban development. Moreover, urban public areas involve squares that serve as the focal point of social life. As a result, providing efficient transportation infrastructure for communities with the help of different modes of transportation becomes a key issue to increase the accessibility levels of these squares. To clarify, urban squares serve as the focal point of social life, necessitating effective access to these squares with well integrated and different modes of transportation. Starting from this viewpoint, this article aims to identify statistically significant factors affecting mode choice behavior of visitors for their trips to the following five squares: Eminönü, Çemberlitaş, Sirkeci, Beyazıt, and Sultanahmet, located in the historical peninsula of Istanbul. This way, the accessibility levels of these squares could be verified with regard to three modes of transportation: walking, private automobile, and public transport. According to the findings of the multinominal logistic regression model, location of home, monthly transport cost, and age are the three factors that have the highest statistically significant marginal effects on the ratios of walking, driving, and using public transport. Unlike prevailing cases in the provinces of developed countries, our findings suggest that education level is not one of the statistically significant parameters that shape the related modal split trends in Istanbul, Turkey.
Practical Applications
Urban squares serve as focal points for social life, necessitating effective access with well-integrated, multimodal transportation network in urban spaces. From this point forth, this article aims to detect the prominent factors shaping the modal split tendency of the visitors when arriving at urban squares located in the historical peninsula of Istanbul. In this way, the accessibility levels of these squares could be verified with regard to three modes of transportation: walking, private automobile, and public transport. According to the preliminary findings of this study, the factor called location of home mostly affects the walking habits of the square visitors, while monthly transportation cost mostly determines the usage of private automobiles in arriving at urban squares. Furthermore, interestingly, age is the leading factor shaping the modal split trend of the usage of public transportation. Unlike the prevailing cases in the provinces of developed countries, our findings suggest that education level is not one of the prominent parameters in our case. In light of these views, the dynamics of urban square arrivals are highly different in the cases of developed countries when compared with those in developing countries, which has been empirically verified by our findings.
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Acknowledgments
This research is part of the ongoing Master’s dissertation of the corresponding author, Bengüsu Turan, supervised by Prof. Dr. Hatice Ayataç (the co-author of the paper).
Notation
The following symbols are used in this paper:
- e
- natural number;
- multiplier impact on marginal change in Xi when the others are fixed;
- multiplicative effect on the odds of a marginal increase in Xi;
- (j)
- each mode of transport (j);
- Log
- logarithm;
- Log
- logarithm;
- Logit [P(Yj = 1)]
- log odds for each mode of transport (j); namely walking, private automobile, and public transport in our study;
- Logit [P(Yi = 1)]
- log odds for each mode of transport (j);
- m2
- metersquare;
- Xi
- model variable i;
- α
- model constant;
- βi
- coefficient of each explanatory variable i;
- Π
- probability;
- Π(Yj = 1)
- multinominal probability of the passenger selecting the transport mode j; and
- Πj
- estimation of each response probability regarding each transport mode j.
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Received: Aug 19, 2021
Accepted: Jun 23, 2022
Published online: Oct 7, 2022
Published in print: Dec 1, 2022
Discussion open until: Mar 7, 2023
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