An exploration of heterogeneity in Latent Psychological Variables on Travelers’ destination choice

Mahpour, Alireza; Baghestani, Amirhossein; Mamdoohi, Amir Reza

doi:10.1016/j.dajour.2023.100179

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…In the literature, various studies have widely used discrete choice models to model decision-making processes (Section 2). The probability of choosing a destination from a large set of alternatives by an individual traveling from a known origin needs to be calculated to solve the destination choice problem [14]. This paper uses a discrete choice logistic model to model the destination choice for discretionary WTs.…”

Section: Modelmentioning

confidence: 99%

“…Improving the outcomes of destination choice models in the context of discretionary WTs is crucial in four key areas: identifying latent and observable variables [14,15], the type of discrete choice model (such as Logit, Probit, and other models), and addressing heterogeneity in destination choice models [16,17] as well as considering choice sets [18][19][20]. The primary objective is to enhance the destination choice model to identify origin-related features of WTs.…”

Section: Introductionmentioning

confidence: 99%

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The Influence of Origin Attributes on the Destination Choice of Discretionary Home-Based Walk Trips

Aghidi Kheyrabadi,

Mamdoohi

2024

IJGI

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Walking has been recognized as an important mode of transportation in recent years, and recent research has improved travel demand models for walk trips. One important added stage is the distribution of walk trips, which can be evaluated using destination choice models. Previous studies have overlooked the importance of origin trip attributes in the destination choice of walk trips. With the aim of improving destination choice models for discretionary home-based walk trips, a questionnaire based on the previous day’s walk trips was used, and 422 trips were collected from individuals. A discrete choice logit model is used for discretionary trips by utilizing policy-related variables, such as origin-sensitive variables, land-use-related variables, and socio-economic conditions of individuals. Additionally, a solution is proposed to address the issue of data scarcity in considering the choice set. The results demonstrate that origin land-use (LU) variables, such as LU diversity index and access to green spaces, as well as socio-economic variables, like age and homeownership status, are statistically significant in the destination choice of discretionary home-based walk trips. One prominent result is that reducing the diversity of unattractive LU compared to increasing the diversity of attractive LU has a greater impact on the destination choice of such trips. Specifically, a 1% increase in the diversity of attractive LU in the origin area leads to a 0.031% increase in the probability of choosing a destination within that area, while a 1% decrease in the diversity of unattractive LU results in a 0.124% increase in the probability of choosing a destination within the area. The findings can be utilized in urban LU distribution and assessing their impact on destination choice for walk trips, ultimately informing future urban planning efforts in the context of pedestrian mobility.

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Section: Modelmentioning

confidence: 99%