Panel analysis in transportation planning: An overview

Kitamura, Ryuichi

doi:10.1016/0191-2607(90)90032-2

Cited by 136 publications

(60 citation statements)

References 34 publications

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“…Although the tradeoffs identified in this paper are described as intra-person tradeoffs, they are actually derived from inter-person comparisons based on the strong assumptions that behavior is symmetric and reversible (Kitamura 1990; i.e., the behavior of a person whose travel time price changes from, say, b m1 to b m2 is the same as that of an otherwise identical person whose travel time price is currently b m2 ). Furthermore, the use of a cross-sectional dataset does not allow us to distinguish between the consequences of shortterm and long-term changes present in the sample.…”

Section: Discussionmentioning

confidence: 99%

Tradeoffs between Time Allocations to Maintenance Activities/Travel and Discretionary Activities/Travel

Chen

Mokhtarian

2006

Transportation

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This paper focuses on the tradeoff in time allocation between maintenance activities/travel and discretionary activities/travel. We recognize that people generally must travel a minimum amount of time in order to allocate one unit of time to the activity. This minimum amount of travel is represented by the travel time price, a ratio obtained by dividing the total amount of time traveling to maintenance or discretionary activities by the total amount of time spent on activities of the same type; it is the time equivalent of the monetary price for performing an activity. Using the San Francisco Bay Area 1996 Household Travel Survey data and applying the Almost Ideal Demand System (AIDS) of demand equations, we found that with respect to the time equivalent of income elasticities of maintenance and discretionary activities, the former is less than unity and the latter is greater than unity. In other words, maintenance activities are a necessity and discretionary activities are a luxury. With respect to the own travel time price elasticities, if the travel time price of performing a certain type of activity increases (for reasons such as traffic congestion), one would reduce the time allocated to that type of activity. Time spent on maintenance activities is less elastic than the time spent on discretionary activities. As for the cross travel time price elasticities (changes in time allocated to activity type i in responses to changes in the time price for activity type j), we found that ε dm > 0 and ε md > 0, suggesting a substitution effect between maintenance and discretionary activities.

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Section: Discussionmentioning

confidence: 99%

Tradeoffs between Time Allocations to Maintenance Activities/Travel and Discretionary Activities/Travel

Chen

Mokhtarian

2006

Transportation

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“…Markov models are criticized for being descriptive, replicating the data, and not being sensitive to behavioral changes (Kitamura;1990;Timmermans et al;1992). Dynamic models using panel data increase statistical efficiency, improve predictions and allow to study behavioral dynamics (Kitamura;1990). In 1990, Kitamura (1990) considered the inclusion of lag terms in discrete choice models not well advanced.…”

Section: Location Choice Modelsmentioning

confidence: 99%

“…Dynamic models using panel data increase statistical efficiency, improve predictions and allow to study behavioral dynamics (Kitamura;1990). In 1990, Kitamura (1990) considered the inclusion of lag terms in discrete choice models not well advanced. Unresolved issues in the estimation of dynamic models using panel data included the representation of the initial conditions and the correlated error term in dynamic models.…”

Section: Location Choice Modelsmentioning

confidence: 99%

“…In Markov models of destination choices, transition matrix represents the probability of choosing a destination given the choice of destination at the previous stop. Markov models are criticized for being descriptive, replicating the data, and not being sensitive to behavioral changes (Kitamura;1990;Timmermans et al;1992). Dynamic models using panel data increase statistical efficiency, improve predictions and allow to study behavioral dynamics (Kitamura;1990).…”

Section: Location Choice Modelsmentioning

confidence: 99%

“…Location choice models are applied to several other different contexts, such as the choice of a departure airport (Furuichi and Koppelman;1994), the choice of a hospital for patients by general practitioner (primary care physicians) (Whynes et al;, the choice of touristic destinations (Woodside and Lysonski;1989;Um and Crompton;1990;Eymann and Ronning;Oppermann;2000;Seddighi and Theocharous;Bigano et al;2006;Chi and Qu;Gössling et al; and in particular recreational outdoor facilities (Fesenmaier;1988;Scarpa and Thiene;2005;Thiene and Scarpa;2009), the choice of migrants (Fotheringham;1986) and the optimal allocation of charging stations for electric vehicles .…”

Section: Location Choicementioning

confidence: 99%

See 2 more Smart Citations

Location choice with longitudinal WiFi data

Danalet

Tinguely

Lapparent

et al. 2016

Journal of Choice Modelling

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While moving from diary survey to location-aware technologies, recent data collection techniques provide new insights about location choices. Only few dynamic models of location choice exist in the literature, and none of them to our knowledge correct for serial correlation. In this paper, we apply a method proposed by Wooldridge (2005) to deal with the initial values problem on the choice of catering locations on a campus using WiFi traces. Cross-validation, price elasticity and simulation of a scenario predicting the opening of a new catering location are presented. Predicted market shares of the new catering location correspond to point-of-sale data of the first week of opening.

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2011

Modelling Transport

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Panel analysis in transportation planning: An overview

Cited by 136 publications

References 34 publications

Tradeoffs between Time Allocations to Maintenance Activities/Travel and Discretionary Activities/Travel

Tradeoffs between Time Allocations to Maintenance Activities/Travel and Discretionary Activities/Travel

Location choice with longitudinal WiFi data

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