01709739

Component

The satisfaction of users is important to operate an effective urban transit system. This information can help the transportation planners and managers in defining effective strategies to meet the user’s needs and preferences. It will also help in formulating plans to retain the existing users and to attract users from other modes of transportation. Behavioral intentions represent a concept that has been investigated for a long time in diverse fields of engineering, social, and behavioral sciences. The service quality, though being a singular concept, represents a rather complex idea, being the quality level of a transit system service characterized by the quality levels of several different service variables. Over the past few years, enterprises, bus operators, and policy makers have started shifting their focus gradually to service quality and user satisfaction. Structural equation modeling (SEM) is a very appropriate and effective technique for solving problems and identifying solutions which are otherwise very complex. SEM is a technique which can bring out the combined effect of users’ behavioral patterns (which are qualitative in nature) and other socio-economic and trip characteristics (which are quantitative in nature) on overall satisfaction. The model projected in this work examines the impact of various variables (qualitative and quantitative) of bus transit in the study areas of Navi Mumbai and Surat, India on the user satisfaction. The study also attempts to identify the significant variables influencing the overall satisfaction levels through SEM. Samples were collected from city bus users (absence of dedicated bus lanes or priorities) from Navi Mumbai and Surat (absence of dedicated bus lanes and with dedicated bus lanes), India. In the absence of dedicated bus lanes, buses ply along with heterogeneous traffic stream sharing road space. This type of bus systems existing in Mumbai and Surat is considered in the present study. In case of BRT system, dedicated bus lanes prevail without transit signal priority in place. This type of bus system existing in Surat city is also considered in this study.

19-01291

English

7p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Bus transit; Bus transit operations; Customer satisfaction; Quality of service; Structural equation modeling; Transit riders

Navi Mumbai (India); Surat (India)

Operations and Traffic Management; Passenger Transportation; Planning and Forecasting; Public Transportation

Transportation Research Board Annual Meeting 2019 Paper #19-01291

TRIS, TRB, ATRI

Jun 27 2019 1:41PM

• A Microsimulation Approach to Access the Environmental Impacts of Different Ramp Metering Scenarios; A Case Study of Eisenhower Expressway in Chicago
• A Novel Methodology to Derive Vehicle Occupancy Using Wi-Fi Sensors Under Heterogenous Traffic Conditions
• Assessing Satisfaction Levels of Bus Users and Monetizing Their Travel Time
• Assessing Travel Time Reliability of a Bus Rapid Transit Route in Surat City, India
• Developing Pedestrian Warrants for Urban Mid-Block Crossings Under Mixed Traffic Environment
• Development of a Top-Down Cracking Rapid Analysis Tool for Rigid Airfield Pavement Systems
• Does Security of Neighborhoods Affect Non-Mandatory Trips? A Copula-Based Joint Multinomial-Ordinal Model of Mode and Trip Distance Choices
• Gap Acceptance Based Safety Evaluation of Urban Midblock Crossings Under Mixed Traffic Environment
• Level of Service Thresholds for Sidewalks Under the Influence of On-Street Parking
• Motorcycle Usage Time and Tour Type: Accelerated Failure Time Approach
• On-Demand Ridesourcing for Emergency Relocation: An Exploratory Analysis of Context and Emotionality
• Proactive Approach for Pedestrian Safety Evaluation Using Choice Model for Unprotected Mid-Block Crossings under Mixed Traffic Conditions
• Review of Rigid Airfield Pavement Cracking Failure Models
• Route Choice Behavior Analysis: An Activity-based Simulation Perspective
• Study on Bus Travel Time Reliability Using GPS-Based Bus Trajectory Data Under Mixed Traffic Conditions