Mode Choice Modeling to Shift Car Travelers towards Park and Ride Service in the City Centre of Karachi

Irfan Ahmed Memon, Saima Kalwar, Noman Sahito, Mir Aftab Hussain Talpur, Imtiaz Ahmed Chandio, Madzlan Napiah and Hasan Tayyeb
Additional contact information
Irfan Ahmed Memon: Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Saima Kalwar: Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Noman Sahito: Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Mir Aftab Hussain Talpur: Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Imtiaz Ahmed Chandio: Department of City and Regional Planning, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Madzlan Napiah: Department of Civil and Environmental Engineering, University Teknologi PETRONAS (UTP), Seri Iskandar 32610, Perak, Malaysia
Hasan Tayyeb: Department of Civil Engineering, Umm Al Qura University, Makkah 21421, Saudi Arabia

Sustainability, 2021, vol. 13, issue 10, 1-26

Abstract: Currently, congestion in Karachi’s central business district (CBD) is the result of people driving their cars to work. Consequently, a park and ride (P&R) service has proved successful in decreasing traffic congestion and the difficulty of finding parking spaces from urban centers. The travelers cannot be convinced to shift towards the P&R service without an understanding of their travel behavior. Therefore, a travel behavior survey needs to be conducted to reduce the imbalance between public and private transport. Hence, mode choice models were developed to determine the factors that influence single-occupant vehicle (SOV) travelers’ decision to adopt the P&R service. Data were collected by an adapted self-administered questionnaire. Mode choice models were developed through logistic regression modeling by using the Statistical Package for the Social Sciences version 22. The findings concluded that more than 70%, specifically motorbike users, to avoid mental stress, and to protect the environment are willing to adopt the P&R service. Moreover, to validate the mode choice models, logit model training and a testing approach were used. In conclusion, by overcoming these influencing factors and balancing push and pull measures of travel demand management (TDM), SOV users can be encouraged to shift towards P&R services. Thus, research outcomes can support policymakers in implementing sustainable modes of public transportation.

Keywords: mode choice modeling; travel behavior; revealed and stated preferences; park and ride Karachi; logistic regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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