How attractive is it to use the internet while commuting? A work-attitude-based segmentation of Northern California commuters

Abstract

Many studies have begun investigating possible transportation landscapes in the autonomous vehicle (AV) era, but empirical results on longer-term decisions are limited. We address this gap using data collected from a survey designed and implemented for Georgia residents in 2017-2018. Focusing on a hypothetical all-AV future, this section of the survey included questions regarding advantages/disadvantages of AVs, short-term mode choice impacts, mediumterm impacts on activity patterns, and long-term behavioral changes-specifically, whether/how AVs will influence individuals to change residential location and the number of cars in the household. We hypothesize that AVs could act in concert with attitudinal preferences to stimulate changes in these long-term decisions, and that some medium-term activity changes triggered by AVs could motivate people to relocate their residence or shed household vehicles. We applied exploratory factor analysis to measure the perceived likelihood that AVs would prompt various medium-term changes. We then included some of those measures, among other variables, in a cross-nested logit (CNL) model of the choice of the residential location/vehicle ownership bundle. Although more than half of respondents expected "no change" in their bundle, we found that younger, lower income, pro-suburban, and pro-non-car-mode individuals were more likely to anticipate changing their selections. In addition, some expected medium-term impacts of AVs influenced changes in these longer-term choices. We further applied the CNL model to two population segments (Atlanta and non-Atlanta-region residents). We found notable improvement in goodness of fit and different effects of factors across segments, signifying the existence of geography-related taste heterogeneity.

Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgia

“…For example, that willingness is likely to differ between people who do nothing special while traveling, those who do work, and those who watch videos while traveling. One of the explanatory variables in our models does, in fact, serve as a proxy for activities while traveling (namely the gain time flexibility factor), and many other studies have also begun to address this issue (see, e.g., Bouscasse and de Lapparent, 2019;Pudāne et al, 2018;Taiebat et al, 2019;Choi and Mokhtarian, 2020). But much is yet to be learned, particularly with respect to the diversity across the population in this regard.…”

Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts

“…Industry classification of I-O accounts. information service activities (1) Research data were provided by the Bureau of Economic Analysis (BEA) of the U.S. Department of Commerce. BEA labels are presented based on the classification in 1977.…”

“…As information and communication technology (ICT) including the technologies, products, and applications that facilitate mobile internet access [1] has rapidly developed, the relationship between transportation and communications has been extensively discussed in the transportation area e.g., [1][2][3]. In the long-term perspective, their relationship can affect sustainable urban development in various ways [4].…”

Fun to drive? The dynamics of car manufacturers' differentiation strategies

“…Possible differentiation in autonomous driving ranges from driver assistant systems to fully autonomous vehicles. Advanced autonomous driving promises productive travel time and more economical transportation (Choi & Mokhtarian, 2020). So‐called (fully autonomous) robo‐taxis are the basis for various future business models, such as autonomously operating taxi services (Liu & Xu, 2020; Nunes & Hernandez, 2020).…”