Are intrazonal trips ignorable?

Bhatta, Bharat P.; Larsen, O I

doi:10.1016/j.tranpol.2010.04.004

Cited by 34 publications

(24 citation statements)

References 15 publications

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“…In a similar vein, Sadek et al [24] found that smart growth-related land use variables (e.g., land use diversity) affects intrazonal travel by encouraging walking or discouraging automobile travel. A more recent study by Bhatta and Larsen [23] also highlighted that "because (intrazonal trips) are shorter trips generally, it is widely believed that intrazonal trips are mostly nonmotorized trips such as walking and cycling" (p. 13). Then, they confirmed this belief through logistic regression analysis on mode choice.…”

Section: Structural Equation Modelingmentioning

confidence: 99%

An Analysis of the Relationship between Land Use and Weekend Travel: Focusing on the Internal Capture of Trips

Gim

2018

Sustainability

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Weekend travel has not been duly considered in academics and practice regarding its relationship with land use. A lack of consideration is notable in terms of how land use internalizes weekend travel. Thus, by separating the internal and external travel of the traffic analysis zone, this study analyzes the land use effect on weekend travel in comparison with that on weekday travel. Two structural equation models, each of which is specified for weekday and weekend travel, construct the same sample and their results become comparable. At the travel variable level, the models find consistent results: Stronger effects are made on internal travel than on external travel and particularly, on trip frequency than on travel time. This implies that compact land use causes a stronger addition of internal trips and a less strong reduction of external trips, that is, changes in destinations rather than in total travel time. At the factor level, unlike the weekday model in which the sociodemographic factor exerts a stronger effect, the weekend model presents that land use more strongly affects travel patterns. This magnitude difference is explained by the different flexibility of compulsory weekday travel and discretionary weekend travel in relation to the choice of trip destination and frequency.

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Section: Structural Equation Modelingmentioning

confidence: 99%

An Analysis of the Relationship between Land Use and Weekend Travel: Focusing on the Internal Capture of Trips

Gim

2018

Sustainability

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“…In practice, transportation modelers mainly focus on centroid-to-centroid flows and tend to exclude intra-zonal trips [30,35]. However, this leads to a biased sample and impedes proper model calibration [36,37]. In our case, this is especially true, since, despite the high resolution at the postal zone level, many shopping trips are very short, and a large proportion of all shopping trips are expected to be intra-zonal (i.e., a large share of groceries is expected to be sold to consumers inside the retailer zone).…”

Section: Intra-zonal Distance Estimationmentioning

confidence: 99%

A Gravity-Based Food Flow Model to Identify the Source of Foodborne Disease Outbreaks

Schlaich

Horn

Fuhrmann

et al. 2020

IJERPH

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Computational traceback methodologies are important tools for investigations of widespread foodborne disease outbreaks as they assist investigators to determine the causative outbreak location and food item. In modeling the entire food supply chain from farm to fork, however, these methodologies have paid little attention to consumer behavior and mobility, instead making the simplifying assumption that consumers shop in the area adjacent to their home location. This paper aims to fill this gap by introducing a gravity-based approach to model food-flows from supermarkets to consumers and demonstrating how models of consumer shopping behavior can be used to improve computational methodologies to infer the source of an outbreak of foodborne disease. To demonstrate our approach, we develop and calibrate a gravity model of German retail shopping behavior at the postal-code level. Modeling results show that on average about 70 percent of all groceries are sourced from non-home zip codes. The value of considering shopping behavior in computational approaches for inferring the source of an outbreak is illustrated through an application example to identify a retail brand source of an outbreak. We demonstrate a significant increase in the accuracy of a network-theoretic source estimator for the outbreak source when the gravity model is included in the food supply network compared with the baseline case when contaminated individuals are assumed to shop only in their home location. Our approach illustrates how gravity models can enrich computational inference models for identifying the source (retail brand, food item, location) of an outbreak of foodborne disease. More broadly, results show how gravity models can contribute to computational approaches to model consumer shopping interactions relating to retail food environments, nutrition, and public health.Int. J. Environ. Res. Public Health 2020, 17, 444 2 of 20 success, which is reflected in the large proportion of unsolved cases [5,6]. Low detection rates can at least partly be explained by the enormous complexity of food supply chains and the high proportion of manual work involved in conventional investigation processes. However, emerging technologies and more readily available supply chain data enable authorities to complement investigation processes with computational models [7]. In the case of widespread outbreaks, these data-scientific approaches promise particular utility in outbreak investigations, given the complex task of tracing through the massive food supply network. Data-scientific approaches support the investigation process in multiple parts: (i) detecting that an outbreak is occurring; (ii) identifying the location source of an outbreak at an early stage of the supply chain like a farm or food processor; (iii) identifying the contaminated food item that caused an outbreak; and (iv) investigating other questions relevant to investigators such as identifying the retailer brand source of an outbreak [8].One type of approach (ii) aims to find the location sou...

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“…Figure 5a shows the daily average inter-district trip distances measured based on approach 1 and approach 2, respectively. The daily average inter-district trip distance measured based on approach 1 assumes trips between two zones have the same origin and destination points (the centroid), which is unrealistic because the origin and destination of trips are usually scattered within a zone and influenced by time of day, trip purpose, and other district attributes (Bharat and Larsen, 2011). The daily average inter-district trip distance measured based on approach 2 is relatively shorter.…”

Section: Trip Distancementioning

confidence: 99%

Understanding Human Mobility Patterns in a Developing Country Using Mobile Phone Data

Demissie

Phithakkitnukoon

Kattan

et al. 2019

Data Science Journal

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This study demonstrates the use of mobile phone data to derive country-wide mobility patterns. We identified significant locations of users such as home, work, and other based on a combined measure of frequency, duration, time, and day of mobile phone interactions. Consecutive mobile phone records of users are used to identify stay and pass-by locations. A stay location is where users spend a significant amount of their time measured through their mobile phone usage. Trips are constructed for each user between two consecutive stay locations in a day and then categorized by purpose and time of the day. Three measures of entropy are used to further understand the regularity of user's spatiotemporal mobility patterns. The results show that user's in a high entropy cluster has high percentage of non-home based trips (77%), and user's in a low entropy cluster has high percentage of commuting trips (49%), indicating high regularity. A set of doubly constrained trip distribution models is estimated. To measure travel cost, the concept of a centroid point that assumes the origins and destinations of all trips are concentrated at an arbitrary location such as the centroid of a zone is replaced by multiple origins and destinations represented by cell tower locations. Note that a cell tower location can only be used as trips origin/destination location when a stay is detected. The travel cost measured between cell tower locations has resulted in shorter trip distances and the model estimation shows less sensitivity to the distance-decay effect.

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Are intrazonal trips ignorable?

Cited by 34 publications

References 15 publications

An Analysis of the Relationship between Land Use and Weekend Travel: Focusing on the Internal Capture of Trips

An Analysis of the Relationship between Land Use and Weekend Travel: Focusing on the Internal Capture of Trips

A Gravity-Based Food Flow Model to Identify the Source of Foodborne Disease Outbreaks

Understanding Human Mobility Patterns in a Developing Country Using Mobile Phone Data

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