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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>How are grocery shopping patterns related to individual diet quality, overall health and mental health? Evidence from four Canadian metropolises</title>
      <link>https://trid.trb.org/View/2655805</link>
      <description><![CDATA[Grocery shopping is a modifiable factor influencing diet and health, yet most studies only considered single or independent attributes of shopping trips, neglecting their interrelated nature. Recent research has identified grocery shopping patterns based on a series of transportation-related characteristics, but their links to diet and health outcomes remain underexplored. This study aims to examine the associations of grocery shopping patterns identified using multidimensional measures of shopping trips with self-rated diet quality, overall health, and mental health, and moreover, tests if the associations between shopping patterns and health are mediated by diet quality. Data are from the 2021 Time Use & Food Habits Survey of Canadian adults living with children under 18 years in four Canadian census metropolitan areas, including Edmonton, Halifax, Vancouver, and Toronto. Structural equation modeling was applied to estimate the associations between shopping patterns, diet quality, and health. Compared to respondents classified as large store shoppers, respondents identified as accompanied shoppers and as frequent shoppers were directly associated with better self-rated diet quality and overall health, but their direct associations with mental health were not significant. They were also indirectly related to better overall and mental health, mediated via better diet quality, while the effect size of accompanied shoppers on mental health is relatively small. Regarding the total associations between shopping patterns and health, frequent shoppers were associated with better overall and mental health, while accompanied shoppers were only related to better overall health. The results imply that grocery shopping patterns with combinations of certain attributes, including relatively high frequency, shopping less at large stores, non-driving travel, and organization in trip chaining, may be beneficial to diet quality and health among households with children. Therefore, interventions should focus on encouraging the combination of certain shopping attributes rather than independent attributes of shopping trips.]]></description>
      <pubDate>Wed, 04 Feb 2026 17:05:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655805</guid>
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    <item>
      <title>Satisfaction, Acceptance and Use Patterns of a New E-Cargo Bike Sharing System – First Results from a German Living Lab Study</title>
      <link>https://trid.trb.org/View/2580237</link>
      <description><![CDATA[Micromobility sharing systems gained increasing attention due to their potential to promote sustainable transport and health and environmental benefits. E-cargo bike sharing systems (ECBSS) remain sparsely researched despite their increased sustainability potential, which offers the opportunity to replace car trips for transporting larger items. The current study investigates the acceptance, usage behavior and contextual influences on using ECBSS. The authors used living lab data (2022–2024) from the SteigtUM project in a small German town. Participants (N = 78) completed surveys on satisfaction, acceptance and usage behavior at different stages of their experience with the system. The results demonstrate a high level of satisfaction with the system. Acceptance measures resulted in consistently positive evaluations. Personal innovativeness and behavioral intention were strongly correlated, indicating that usage intention is higher for participants who adopt new technologies quickly. Behavioral usage patterns showed a modal shift from commuting trips in 2022 to shopping-related trips in the following years. Approximately 20–30% of car trips were replaced with the system, reflecting a high potential to contribute to sustainability goals for the investigated user group. Weather conditions had a limited impact on usage. In sum, study results highlight ECBSS as an alternative to reduce motorized transport, especially in smaller cities. Targeted strategies are needed, however, to overcome barriers to adoption and encourage a broader range of potential user groups. Future research should investigate long-term effects and include safety aspects to optimize user experience and acceptance.]]></description>
      <pubDate>Thu, 29 Jan 2026 17:02:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580237</guid>
    </item>
    <item>
      <title>Characterizing destinations and modes of shopping trips replaced by e-shopping</title>
      <link>https://trid.trb.org/View/2608351</link>
      <description><![CDATA[The growing popularity of e-shopping holds the potential to reduce shopping trips. It is very important for informing urban planning and optimizing transportation systems to identify the destinations and modes of shopping trips replaced by e-shopping. To the best of our knowledge, however, very little prior research examines this issue. This study attempts to characterize the destinations and modes of shopping trips substituted by e-shopping, based on stated preference survey data from Chengdu, China. The findings indicate that e-shopping significantly substitutes shopping trips, with variations depending on destination type and travel mode. Specifically, e-shopping shows a stronger substitution effect for trips to nearby shopping malls or by public transit. Notably, the destinations of replaced shopping trips vary by product type, with a significantly stronger substitution effect on trips to community stores (e.g., convenience stores or retail outlets near residential areas) for daily goods. Similarly, the travel modes of replaced shopping trips differ by destination, with a substantially stronger substitution effect on active mode trips to community stores. The study also highlights diverse factors influencing these substitution effects, offering valuable insights for urban transportation planning and policymaking.]]></description>
      <pubDate>Mon, 17 Nov 2025 16:38:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2608351</guid>
    </item>
    <item>
      <title>Revisiting the effects of e-shopping on shopping trips: Empirical evidence from Chengdu, China</title>
      <link>https://trid.trb.org/View/2599015</link>
      <description><![CDATA[The rapid proliferation of e-commerce has profoundly changed the way people shop and travel. To date, numerous empirical studies have examined the impact of e-shopping on shopping trips. However, there is still no consensus on this topic, which is probably because the existing analytical methods cannot effectively measure the relationship. This study aims to revisit the travel effects of e-shopping using current shopping behavior as a reference point, ensuring the temporal precedence of causal inference. Utilizing data from 742 respondents in Chengdu, China, the authors found that 41.5 %–68.2 % of the respondents would be inclined to increase their frequencies of shopping travel for four categories of products (i.e., clothes, books, packaged foods, and daily necessities) if these goods were not available online, suggesting stronger substitution effects. Additionally, the substitution effect varies notably among product categories, with clothes showing a stronger substitution effect compared to others. In addition, regression outcomes suggest that longer smartphone use history, greater e-shopping enjoyment, and lower street density increase the likelihood of substituting shopping travel.]]></description>
      <pubDate>Tue, 07 Oct 2025 08:21:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599015</guid>
    </item>
    <item>
      <title>Geographic Scale Matters in Analyzing the Effects of the Built Environment on Choice of Travel Modes: A Case Study of Grocery Shopping Trips in Salt Lake County, USA</title>
      <link>https://trid.trb.org/View/2593905</link>
      <description><![CDATA[Compared to commuting, grocery shopping trips, despite their profound implications for mixed land use and transportation planning, have received limited attention in travel behavior research. Drawing upon a travel diary survey conducted in a fast-growing metropolitan region of the United States, i.e., Salt Lake County, Utah, this research investigated a variety of influential factors affecting mode choices associated with grocery shopping. The authors analyze how built environment (BE) characteristics, measured at seven spatial scales or different ways of aggregating spatial data—including straight-line buffers, network buffers, and census units—affect travel mode decisions. Key predictors of choosing walking, biking, or transit over driving include age, household size, vehicle ownership, income, land use mix, street density, and distance to the central business district (CBD). Notably, the influence of BE factors on mode choice is sensitive to different spatial aggregation methods and locations of origins and destinations. The straight-line buffer was a good indicator for the influence of store sales amount on mode choices; the network buffer was more suitable for the household built environment factors, whereas the measurement at the census block and block group levels was more effective for store-area characteristics. These findings underscore the importance of considering both the spatial analysis method and the location (home vs. store) when modeling non-work travel. A multi-scalar approach can enhance the accuracy of travel demand models and inform more effective land use and transportation planning strategies.]]></description>
      <pubDate>Mon, 15 Sep 2025 10:28:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2593905</guid>
    </item>
    <item>
      <title>Incorporating Infrastructure and Vehicle Technology Requirements, Changes in Demand, and Decarbonization Policies’ Considerations into Freight Planning [supporting dataset]</title>
      <link>https://trid.trb.org/View/2592294</link>
      <description><![CDATA[This report develops an equitable and sustainable freight-oriented land use (LU) methodology to support future planning activities, enabling the integration of freight activity across urban, suburban, and rural areas and facilitating the transition of heavy- and medium-duty vehicles toward zero-emission. The methods include a literature review to identify freight sustainable strategies, policy analysis at different scales, characterization of local context, and demand/supply patterns. The latter examines the spatial distribution and land use characteristics of freight facilities and retail/service sectors in the Sacramento region to inform sustainable and equitable planning strategies. This analysis identifies co-location patterns, accessibility gaps, and sectoral interactions using a multi-dimensional approach integrating spatial clustering, distance analysis, population-employment dynamics, and environmental burdens. Data sources include Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES), American Community Survey (ACS), CalEnviroScreen, and OpenStreetMap, alongside geospatial tools in R. The findings suggest the need for targeted interventions to address potential conflicts, service deserts, and environmental justice concerns. The study proposes actionable strategies for planners to support balanced economic development and improve access to essential services.]]></description>
      <pubDate>Wed, 10 Sep 2025 09:22:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2592294</guid>
    </item>
    <item>
      <title>Accessibility of food - A multilevel approach comparing a choice based model with perceived accessibility in Mainfranken, Germany</title>
      <link>https://trid.trb.org/View/2577275</link>
      <description><![CDATA[Accessibility is a multifaceted concept. Accessibility of food in particular serves as a critical indicator of quality of life and is therefore influencing daily life in diverse ways. In geographic retail research, empirical methods as well as modeling techniques are of great importance for the analysis and evaluation of accessibility and market areas. Firstly, this paper introduces an econometric choice-based flow and catchment model for assessing the accessibility of grocery stores. Secondly, acknowledging that spatial perceptions of food supply can vary significantly among individuals, the study compares modeled accessibility with perceived accessibility using data from a household survey. A total of 2300 individuals from the Mainfranken region in Germany were surveyed regarding their grocery shopping habits. Three central questions were posed regarding satisfaction with and effort required for food access to evaluate perceived accessibility. The comparison of modeled accessibility with perceived accessibility highlights the complexity of perception, revealing that it is shaped by various factors. For instance, some residents of areas with objectively good accessibility rated their supply situation as poor, while those in less accessible areas often expressed higher satisfaction. This study contributes two key insights: First, it introduces a novel, comprehensive approach to accessibility that considers both the supplier and consumer perspectives based on actual shopping behavior. Second, it demonstrates that perceived accessibility is shaped by individual characteristics and is strongly influenced by lifestyle, personal resilience and daily routines. In particular, highly mobile individuals and population groups exhibit greater resilience and are more willing to travel longer distances to meet their needs.]]></description>
      <pubDate>Wed, 13 Aug 2025 09:25:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2577275</guid>
    </item>
    <item>
      <title>Impact of the COVID-19 pandemic on e-commerce adoption in emerging economies</title>
      <link>https://trid.trb.org/View/2572401</link>
      <description><![CDATA[The COVID-19 pandemic caused major disruptions to daily life, limiting in-person shopping and accelerating the shift to online retail. As lockdowns and social distancing measures were put in place, many consumers turned to e-commerce as an alternative. This study examines how the pandemic affected consumer behavior and evaluates how economic incentives influence the decision to shop online. Using survey data from the Medellín Metropolitan Area in Colombia, the authors estimate two ordinal logistic regression models to understand (1) how often consumers visited physical stores before making online purchases and (2) how frequently they shopped online. The results show that delivery costs, access to digital devices, and the types of products purchased online all affect whether consumers still visit stores. In contrast, online shopping frequency is more strongly associated with income and the purchase of specific items, such as pet and grocery products. Among the incentives tested, free shipping was more effective than discounts in encouraging consumers to shop exclusively online. These findings provide valuable insights into e-commerce adoption and can help inform strategies to improve urban logistics and support sustainable growth in the online retail sector, particularly in emerging economies.]]></description>
      <pubDate>Mon, 21 Jul 2025 08:55:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572401</guid>
    </item>
    <item>
      <title>Is mobility a good proxy for consumption?</title>
      <link>https://trid.trb.org/View/2569930</link>
      <description><![CDATA[This paper investigates the relationship between mobility and consumer expenditure using a longitudinal dataset of local-level transactions in the United Kingdom. It distinguishes between online and in-store spending and employs fixed effects models covering the period from February 2020 to March 2022. The analysis finds that retail and recreational mobility consistently serve as reliable proxies for in-store spending, while there is limited evidence of a correlation between online spending and mobility. These findings suggest that mobility data can serve as a valuable proxy for consumer activity in countries lacking high-frequency consumption data.]]></description>
      <pubDate>Wed, 16 Jul 2025 19:49:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569930</guid>
    </item>
    <item>
      <title>Profiling shopping mobility in pre- and post-purchase phases: Latent class analysis of apparel trial and return trips</title>
      <link>https://trid.trb.org/View/2560921</link>
      <description><![CDATA[This study explores the unobserved heterogeneity in shopping mobility by examining consumers’ apparel trial and return behaviors across the pre- and post-purchase phases. In the context of the rapid growth of e-commerce and rising return rates, understanding how trial and return behaviors interact within individual shopping journeys becomes critical. While prior research has explored online shopping’s impact on travel, limited attention has been paid to the diversity of these behaviors and their mobility implications. To address this gap, two latent class choice models are estimated using revealed preference data from 507 U.S. shoppers. Latent class membership is explained through attitudinal profiles derived from factor analysis (Bartlett scores), capturing environmental concerns, consumption habits, and convenience preferences. Three distinct segments are identified for both trial and return behaviors, each characterized by unique trip frequencies, trial and return method preferences, and socio-demographic traits. The interplay between pre- and post-purchase mobility is further examined through a segment probability matrix. Results show that most shoppers specialize in either trial or return behaviors, with limited overlap. For instance, “Active Trial Enthusiasts” comprise 51.2% of the sample, marked by frequent store visits and hybrid trial preferences. In contrast, 23.6% belong to the “Frequent & Opportunistic Returners,” who regularly return goods using both self-managed and carrier-based methods. These findings reveal diverse and complementary mobility patterns shaped by apparel shopping habits. The study provides valuable insights for transport planners and e-retailers seeking to address the environmental and operational impacts of evolving consumer behavior.]]></description>
      <pubDate>Thu, 26 Jun 2025 16:35:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2560921</guid>
    </item>
    <item>
      <title>Evaluating perceived accessibility to workplace and shopping destinations in informal urban communities in Ghana and Tanzania</title>
      <link>https://trid.trb.org/View/2548149</link>
      <description><![CDATA[Transport-related accessibility is important, as it enables individuals to live their daily lives and travel to activity destinations they value. Access to valued opportunities is a prerequisite to address social inclusion and quality of life. Unlike conventional accessibility measures, perceived accessibility focuses on the perceived possibilities and ease of engaging in preferred activities using different transport modes. Perceived access to essential destinations such as workplaces and shopping, and its integration with objective measures are severely under-studied in sub-Saharan African cities. Kumasi-Ghana and Dar es Salaam-Tanzania offer an ideal case for investigating the effects of accessibility to workplace and shopping destinations in the context of informal urban communities. This study measures perceived accessibility, determines its comparability to objective measures, and examines the underlying socio-demographic factors to better understand the factors influencing commuters' perceptions of accessibility. The authors' findings established a relationship between perceived and objective accessibility to workplaces and shopping in both cities. Commuters' ratings of accessibility in Dar es Salaam-Tanzania were lower than those from Kumasi-Ghana. This was in agreement with higher travel times to these destinations in Dar es Salaam-Tanzania compared to Kumasi-Ghana. The authors found that the decreasing order of influence on travel perception in both cities is travel characteristics, community transport, and the built environment. Also, the decreasing order of impact on travel is travel cost, time, and frequency, highlighting travel cost as the primary concern for residents in both cities. Relatedly, the decreasing order of influence on travel perception is comfort, satisfaction, and success in Kumasi-Ghana whereas in Dar es Salaam-Tanzania it is travel success, satisfaction, and comfort. The findings establish similarities between commuters' subjectively determined accessibility and the established objective measures (e.g., travel cost, time, etc.).]]></description>
      <pubDate>Thu, 26 Jun 2025 11:42:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548149</guid>
    </item>
    <item>
      <title>Towards a sustainable urban mobility: comparing online and in-store shopping choices</title>
      <link>https://trid.trb.org/View/2558511</link>
      <description><![CDATA[In recent years, e-shopping has gained increasing popularity, with more people gradually shifting from traditional shopping channels to online platforms causing significant impacts on city sustainability due to small, frequent, sprawled, and failed deliveries. In fact, due to the necessity of using sometimes-inefficient delivery trips to deliver products to consumers (such as at their residences), this can have a substantial influence on freight traffic in metropolitan regions. Using data from interviews with 509 respondents carried out in Sardinia (Italy) in 2022, the current study investigates how end consumers’ choices between online and physical (in-store) shopping are related. In doing this, two different econometrics models for simulating online and in-store shopping were constructed: a multivariate ordered probit model to understand which covariates influence the propensity to purchase different kinds of products online and in-store; a binary probit model to identify who is more likely to reduce the number of trips due to e-shopping. From the descriptive statistical analysis, it emerged that a majority of individuals in the sample (62.3 %) reduced their number of physical shopping trips due to e-shopping (substitution effect). The multivariate ordered probit model shows that socio-demographic characteristics, land-use attributes, and psychological variables significantly influence shopping behavior. Specifically, the perception of online shopping accessibility and quality positively correlates with the likelihood of purchasing certain product categories online. Conversely, the perceived importance of touching products and in-store safety positively affects in-store shopping preferences. Additionally, positive correlation terms among online and in-store shopping tendencies for the same product categories suggest that consumers inclined to buy certain items online are also more likely to purchase them in-store. The binary probit model highlights substantial heterogeneity in the likelihood of reducing physical shopping trips. Individuals with more experience shopping online, higher perceptions of online quality, and lower importance placed on touching products are more likely to reduce in-store visits. From a policy perspective, this study emphasizes the need for urban planners and policymakers to integrate consumer shopping behavior into strategies aimed at managing urban mobility, logistics, and last-mile delivery systems.]]></description>
      <pubDate>Fri, 20 Jun 2025 11:58:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2558511</guid>
    </item>
    <item>
      <title>The race travel penalty for food shopping in metropolitan areas of the United States</title>
      <link>https://trid.trb.org/View/2549044</link>
      <description><![CDATA[A tenet of transportation planning is that most consumers choose the closest destination when they can. However, when it comes to food shopping, the choice of store is determined by a broad set of characteristics and most shoppers are willing to make long trips to stores beyond their local neighborhoods, making travel an especially important determinant in accessing healthy and affordable food. Since residences and store locations are patterned by race in the United States, this study asks whether racial minorities must endure longer travel for food shopping compared to White travelers. Using a nationally representative data set from the American Time Use Survey (ATUS) and multiple regression, the analysis finds that Black, Asian, and Hispanic shoppers must spend substantially longer travel time when driving to a food store compared to White shoppers. Effective policy interventions require placing attention on supporting travel for disadvantaged residents so they can reach a varied set of food stores with nutritious offerings at competitive prices beyond the local neighborhood.]]></description>
      <pubDate>Thu, 05 Jun 2025 17:05:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2549044</guid>
    </item>
    <item>
      <title>Why do shoppers keep making online shopping trips? Learning from evidence in Bandung, Indonesia</title>
      <link>https://trid.trb.org/View/2548326</link>
      <description><![CDATA[Studies from most developed countries provide evidence that e-shopping decreases the need for shopping trips. Considering the unique characteristics of infrastructure as well as cultural background, this study investigates the hypothesis that there is another impact of online shopping on shopping trip behavior, namely, on the travel behavior of shoppers. The investigation used data from Bandung, Indonesia, to represent developing countries. The study found that online shoppers keep making trips as a substitution for, as well as a complement to, their in-store shopping. Shoppers’ decisions are found to be significantly influenced by their e-shopping experience, both positively and negatively. This study also found that e-shopping spending is influenced by in-store shopping frequency and spending.]]></description>
      <pubDate>Thu, 29 May 2025 17:25:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548326</guid>
    </item>
    <item>
      <title>A novel pattern recognition technique to characterize multi-day shopping and entertainment trip activities</title>
      <link>https://trid.trb.org/View/2536277</link>
      <description><![CDATA[The driving force behind individuals’ travel behavior is closely linked to the need to engage in various activities, such as working, shopping, and entertainment. While the importance of shopping and entertainment activities is well-documented in activity-based modeling research, there is no existing literature specifically addressing different shopping activities and entertainment trips over long time periods, such as an entire week, with a granular level of investigation. This study introduces a novel framework using comprehensive pattern recognition modeling, aiming to identify households’ level weekly shopping and entertainment trip activity patterns and to identify their representative patterns. Utilizing data from the 2019 Puget Sound Regional Household Travel Survey, the one-week activity patterns are split into 336 30-minute intervals. Each interval is comprised of information on trip activity types, duration, and start time. Pattern complexity of activity sequences in the dataset is recognized using the two-staged clustering process involving affinity propagation (AP) and k-means algorithms, which results in six unique clusters of homogeneous weekly activity patterns. These clusters exhibit a heterogeneous diversity in the temporal distribution of trip activity durations and significant differences in a variety of sociodemographic variables. Moreover, using sequence alignment techniques, we identified the representative trip activity pattern of the households in each cluster. Notably, younger individuals tend to shop on weekends, while older adults (age 65+) maintain consistent daily shopping habits. Households with higher incomes and vehicle access typically shop midweek, whereas a significant portion of high-income households without vehicles opt for Monday shopping. This comprehensive analysis highlights the intricate relationship between recreational travel behavior and sociodemographic factors, shedding light on nuanced patterns of activity engagement over extended time periods.]]></description>
      <pubDate>Wed, 14 May 2025 13:09:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2536277</guid>
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