4.7 Article

A comparison of online and in-person activity engagement: The case of shopping and eating meals

期刊

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2020.02.023

关键词

Physical and virtual activity engagement; Shopping activities; Eat-meal activities; Multivariate ordered probit model; ICT effects on travel behavior; Substitution and complementarity effects

资金

  1. Center for Teaching Old Models New Tricks (TOMNET) - U.S. Department of Transportation [69A3551747116]
  2. Data-Supported Transportation Operations and Planning (D-STOP) Center - U.S. Department of Transportation [DTRT13GUTC58]
  3. Brazilian Funding Agency CAPES
  4. Ministry of Human Resource Development (MHRD) of the Government of India through its Scheme for Promotion of Academic and Research Collaboration (SPARC) program

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The virtual (online) and physical (in-person) worlds are increasingly inter-connected. Although there is considerable research into the effects of information and communication technologies (ICT) on activity-travel choices, there is little understanding of the inter-relationships between online and in-person activity participation and the extent to which the two worlds complement one another or substitute for one another. Shopping is one of the activity realms in which the virtual and physical spaces are increasingly interacting. This paper aims to unravel the relationships between online and in-person activity engagement in the shopping domain, while explicitly distinguishing between shopping for non-grocery goods, grocery products, and ready-to-eat meals. Data from the 2017 Puget Sound household travel survey is used to estimate a multivariate ordered probit model of the number of days in a week that a sample of households engages in in-person activity engagement and online activity engagement for each of these shopping activity types - leading to a model of six endogenous outcomes. Model results show that there are intricate complementary and substitution effects between in-person and online shopping activities, that these activities are considered as a single packaged bundle, and that the frequencies of these activities are significantly affected by income, built environment attributes, and household structure. The findings suggest that travel forecasting models should incorporate model components that capture the interplay between in-person and online shopping engagement and explicitly distinguish between non-grocery and grocery shopping activities. Policies that help bridge the digital divide so that households of all socio-economic strata can access goods and services in the virtual world would help improve quality of life for all. Finally, the paper highlights the need to bring passenger and freight demand modeling, at least within urban contexts, into a single integrated structure.

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