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Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases
15 references·0 citing·55 second hop
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References

  • 1979Optimization by the Analytic Hierarchy Process4,520 cited
  • 2010Gender and mobility: new approaches for informing sustainability797 cited
  • 2014Intention to use a fully automated car: Attitudes and a priori acceptability695 cited
  • 2016Factors influencing the choice of shared bicycles and shared electric bikes in Beijing489 cited
  • 2016The Analytic Hierarchy and Analytic Network Processes for the Measurement of Intangible Criteria and for Decision-Making448 cited
  • 2021Transport infrastructure connectivity and conflict resolution: a machine learning analysis196 cited
  • 2015A gender analysis of everyday mobility in urban and rural territories: from challenges to sustainability136 cited
  • 2018Violent mobilities: men, masculinities and road conflicts in Sweden58 cited
  • 2014Public attitudes to and perceptions of high speed rail in the UK44 cited
  • 2019Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System34 cited
  • 2021The Concept of Fairness in Relation to Women Transport Users27 cited
  • 2019Advancing cycling among women: An exploratory study of North American cyclists21 cited
  • 2021Data-Driven Analysis on Inter-City Commuting Decisions in Germany15 cited
  • 2021Application of Mathematical and Computational Methods to Identify Women’s Priorities in Transport

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  • 2010Gender and Transport10 cited
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