Comparison Between Logistic Regression And Spike Models For The Probability Of Prediction Travelling Behavior
Keywords:
willingness-to-pay, logit model, travel timAbstract
The objective of the present empirical study was to test “bridging assumptions,” that’s, to see how closely the analysis of the objective macro-structural conditions determining the travel mode choice comply with the situation as perceived by the M respondents. The adopted methodology is based on a contingent valuation (CV) survey. Stated Preference (SP) surveys, also called self-stated preferences for research or services, have been widely applied in the areas of marketing and travel demand modelling, separately or jointly with RP surveys with observed choices of product purchase or service use. Stated preference (SP) survey is essential for, and helpful in, evaluating the willingness-to-pay for mode changing, and investigating people’s acceptability and perceptions. Two SP surveys (attitudinal and hypothetical choices) were implemented on car users. An attitudinal survey asked the respondents to express their responses to various situations (e.g., if they would shift to public transport if the service improved). The two models were compared based on their predictability and accuracy indicators and the results revealed that spike model manifested higher accuracy than logit model for predication.
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References
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