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Exploring determinants of feeder mode choice behavior using Artificial Neural Network: Evidences from Delhi metro
16 references·8 citing·37 second hop
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(1956)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)The magical number seven, plus or minus two: Some limits on our capacity for processing information. 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References

  • 1977An Application of Hierarchical Kappa-type Statistics in the Assessment of Majority Agreement among Multiple Observers4,327 cited
  • 2005The Kappa Statistic in Reliability Studies: Use, Interpretation, and Sample Size Requirements4,093 cited
  • 1988Discrete choice analysis: Theory and application to travel demand3,257 cited
  • 2004Factors influencing light-rail station boardings in the United States443 cited
  • 2004The bicycle as a feedering mode: experiences from three European countries390 cited
  • 1998Public Transportation Access388 cited
  • 2008Access to railway stations and its potential in increasing rail use374 cited
  • 2005Urban transport crisis in India340 cited
  • 2007The access journey to the railway station and its role in passengers’ satisfaction with rail travel312 cited
  • 2010Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground285 cited
  • 2010Factors generating boardings at Metro stations in the Seoul metropolitan area248 cited
  • 2004Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio247 cited
  • 2000Seamless, accessible travel: users’ views of the public transport journey and interchange232 cited
  • 2006Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study

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200 cited
  • 2007Analysis of light rail rider travel behavior: Impacts of individual, built environment, and crime characteristics on transit access194 cited
  • 2012Performance indicators for an objective measure of public transport service quality192 cited
  • Cited by

    • 2023Ebike Sharing vs. Bike Sharing: Demand Prediction Using Deep Neural Networks and Random Forests21 cited
    • 2024A comparative MADM approach for prioritizing factors influencing service quality of Intermediate Public Transport as access mode to metro stations in Delhi, India16 cited
    • 2024Navigating Passenger Satisfaction: A Structural Equation Modeling–Artificial Neural Network Approach to Intercity Bus Services15 cited
    • 2023Development of service quality model computing ridership of metro rail system using fuzzy system12 cited
    • 2025The research landscape of first- and last-mile in public transport systems: A bibliometric analysis10 cited
    • 2025Priority areas of intervention for development of walking, bicycling and motorized feeder facilities as first-and-last mile connectivity with metro stations9 cited
    • 2024Determinants of paratransit feeder service provision using AI-synthesized revealed preference data: a paratransit drivers’ perspective on PT reform using machine learning6 cited
    • 2024Evolutionary dynamics of the travel mode choice behavior based on the replicator-mutator model4 cited