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- W4382702364 abstract "In recent years, revealed preference (RP) and stated preference (SP) surveys have been extensively employed in variety of sectors where consumer choice is involved so as to estimate demand for a service/product. This paper focuses on investigating the differences in modelling outputs arising from the use of RP, SP and joint RP-SP datasets. A case study of first and last mile mode choice to the upcoming metro rail stations in Mumbai is considered. Data was collected from random individuals residing in the adjoining neighbourhoods of five upcoming metro stations. Multinomial logit (MNL) models are estimated considering only RP data, only SP data and joint RP-SP data. Results show that estimates of several parameters of the standalone SP and RP models either overestimate or underestimate the propensity of using an alternative. However, the joint model provides intuitive parameter estimates, and the overall goodness of fit of the joint model is significantly greater than stand-alone models. Joint models have a greater number of variables explaining the choice behaviour when compared to standalone models. Also, the joint RP–SP model enables in developing the scale factor, which accounts for the temporal differences between the RP and SP data, and eliminates the hypothetical biasness and behavioural differences that could have a major impact on the findings of the standalone RP and SP models." @default.
- W4382702364 created "2023-07-01" @default.
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- W4382702364 date "2023-01-01" @default.
- W4382702364 modified "2023-09-26" @default.
- W4382702364 title "Joint Versus Standalone Estimation of First/Last Mile Mode Choice Utilising Revealed and Stated Preference Datasets" @default.
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- W4382702364 doi "https://doi.org/10.1007/978-981-99-2556-8_6" @default.
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