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Predicting customer purpose of travel in a low-cost travel environment—A Machine Learning Approach
16 references·0 citing·52 second hop
Predicting customer purpose of travel in a low-cost travel environment—A Machine Learning Approach (2022)Predicting customer purpose of travel in …A systematic review of machine learning classification methodologies for modelling passenger mode choice (2020)A systematic review of machin…Applying a random forest method approach to model travel mode choice behavior (2018)Applying a random forest meth…A comparative study of machine learning classifiers for modeling travel mode choice (2017)A comparative study of machin…Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China (2015)Using hierarchical tree-based…Review of GPS Travel Survey and GPS Data-Processing Methods (2014)Review of GPS Travel Survey a…Deriving Personal Trip Data from GPS Data: A Literature Review on the Existing Methodologies (2014)Deriving Personal Trip Data f…Neural network based temporal feature models for short-term railway passenger demand forecasting (2008)Neural network based temporal…EU network carriers, low cost carriers and consumer behaviour: A Delphi study of future trends (2007)EU network carriers, low cost…Customer segmentation revisited: The case of the airline industry (2007)Customer segmentation revisit…Passengers’ perceptions of low cost airlines and full service carriers: A case study involving Ryanair, Aer Lingus, Air Asia and Malaysia Airlines (2005)Passengers’ perceptions of lo…The effect of airline service quality on passengers’ behavioural intentions: a Korean case study (2004)The effect of airline service…A comparison of forecasting methods for hotel revenue management (2003)A comparison of forecasting m…Price elasticities of demand for passenger air travel: a meta-analysis (2002)Price elasticities of demand …Marketing low-cost airline services to business travellers (2001)Marketing low-cost airline se…Determining Future Travel Behavior from Past Travel Experience and Perceptions of Risk and Safety (1998)Determining Future Travel Beh…Econometric Models of Probabilistic Choice (1981)Econometric Models of Probabi…Time Series Forecasting with Neural Networks: A Comparative Study Using the Air Line Data (1998)The M3-Competition: results, conclusions and implications (2000)Principles of Forecasting (2001)Forecasting demand of commodities after natural disasters (2009)SARIMA modelling approach for railway passenger flow forecasting (2016)Passenger demand forecasting in scheduled transportation (2019)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Limited-dependent and qualitative variables in econometrics (1983)Combining forecasts: A review and annotated bibliography (1989)Restaurant Revenue Management at Chevys: Determining the Best Table Mix (2004)Predicting Hotel Demand Using Destination Marketing Organization’s Web Traffic Data (2013)Using machine learning and big data for efficient forecasting of hotel booking cancellations (2020)The Penn World Table (Mark 5): An Expanded Set of International Comparisons, 1950-1988 (1991)Concepts of Price Elasticities of Transport Demand and Recent Empirical Estimates: An Interpretative Survey (2005)Tourists' Perception of International Air Travel's Impact on the Global Climate and Potential Climate Change Policies (2007)High-speed rail and air transport competition: Game engineering as tool for cost-benefit analysis (2010)Consumer behaviour and demand response of tourists to climate change (2011)SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality (1988)Measuring Service Quality: A Reexamination and Extension (1992)Marketing Research: An Applied Orientation (1994)Expectations and perceptions in airline services: An analysis using weighted SERVQUAL scores (2007)Service quality, satisfaction, and behavioural intentions (2009)An SEM–artificial-neural-network analysis of the relationships between SERVPERF, customer satisfaction and loyalty among low-cost and full-service airline (2015)Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands (2009)Transportation mode detection using mobile phones and GIS information (2011)Where do cyclists ride? 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References

  • 1981Econometric Models of Probabilistic Choice2,052 cited
  • 1998Determining Future Travel Behavior from Past Travel Experience and Perceptions of Risk and Safety1,038 cited
  • 2018Applying a random forest method approach to model travel mode choice behavior491 cited
  • 2017A comparative study of machine learning classifiers for modeling travel mode choice423 cited
  • 2004The effect of airline service quality on passengers’ behavioural intentions: a Korean case study423 cited
  • 2005Passengers’ perceptions of low cost airlines and full service carriers: A case study involving Ryanair, Aer Lingus, Air Asia and Malaysia Airlines418 cited
  • 2002Price elasticities of demand for passenger air travel: a meta-analysis357 cited
  • 2014Review of GPS Travel Survey and GPS Data-Processing Methods350 cited
  • 2003A comparison of forecasting methods for hotel revenue management287 cited
  • 2008Neural network based temporal feature models for short-term railway passenger demand forecasting211 cited
  • 2007Customer segmentation revisited: The case of the airline industry197 cited
  • 2014Deriving Personal Trip Data from GPS Data: A Literature Review on the Existing Methodologies162 cited
  • 2020A systematic review of machine learning classification methodologies for modelling passenger mode choice154 cited
  • 2001Marketing low-cost airline services to business travellers

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137 cited
  • 2007EU network carriers, low cost carriers and consumer behaviour: A Delphi study of future trends115 cited
  • 2015Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China105 cited
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