Smart Devices and Travel Time Use by Bus Passengers in Vancouver, Canada

Guo, Zhan; Derian, Alexandra; Zhao, Jinhua

doi:10.1080/15568318.2013.784933

Cited by 48 publications

(37 citation statements)

References 26 publications

(75 reference statements)

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“…Although research on travel-based multitasking used to focus on public transit passengers (e.g., Guo, Derian, & Zhao, 2015;Lyons, Jain, & Weir, 2016), multimodal studies are increasing (Keseru & Macharis, 2018). Naturally, modal differences in activity participation appear, likely due to differences in required levels of operation and attention (Circella, Mokhtarian, & Poff, 2012).…”

Section: How Productive and Useful Is Travel-based Multitasking Anyway?mentioning

confidence: 99%

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

Singleton

2018

Transport Reviews

131

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Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time-a primary component of the "positive utility of travel" concept-thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs' VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different "positive utility"-subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.

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Section: How Productive and Useful Is Travel-based Multitasking Anyway?mentioning

confidence: 99%

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

Singleton

2018

Transport Reviews

131

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“…There were few studies of travel-based multitasking until recently (Kenyon & Lyons, 2007). Studies use different data collection methods, including field observations (Guo, Derian, & Zhao, 2015;Ohmori & Harata, 2008;Russell et al, 2011;Timmermans 6 A few scholars have wondered whether some forms of passive travel are even activities (Kenyon, 2010, p. 54;Circella et al, 2012, p. 84). For instance: The major conceptual difference between riding on/in a train/bus/taxi and cleaning clothes using a home washing machine is that passenger travel requires copresence of the traveler and the means of transportation at all times.…”

Section: Travel-based Multitaskingmentioning

confidence: 99%

“…& van der Waerden, 2008;van der Waerden, Timmermans, & van Neerven, 2009), questionnaire surveys and activity diaries (Berliner, Malokin, Circella, & Mokhtarian, 2015;Diana, 2008;Ettema, Friman, Gärling, Olsson, & Fujii, 2012;Ettema & Verschuren 2007;Frei, Mahmassani, & Frei, 2015;Guo et al, 2015;Kenyon, 2008;Kenyon & Lyons, 2007;Keseru et al, 2015;Lyons, Jain, & Holley, 2007;Lyons et al, 2013;Lyons, Jain, & Weir, 2016;Malokin et al, 2015;Mokhtarian, Papon, Goulard, & Diana, 2015;Ohmori & Harata, 2008;Yosritzal, 2014;Zhang & Timmermans, 2010), and interviews or focus groups (Handy et al, 2005;Jain & Lyons, 2008). While observations can reduce response bias and more accurately capture activity durations, self-reported survey data may be more useful for studying PUT because activities may be more closely related to underlying motivations (recall the activities vs. items discussion).…”

Section: Travel-based Multitaskingmentioning

confidence: 99%

“…Methods include qualitative interviews or focus groups (Gardner & Abraham, 2007;Handy et al, 2005;Hiscock, Macintyre, Kearns, & Ellaway, 2002;Jain & Lyons, 2008;Mann & Abraham, 2006) as well as questionnaire surveys (Ellaway, Macintyre, Hiscock, & Kearns, 2003;Loo et al, 2015;Steg, 2005). Many studies focus on motivations for driving and car use (Gatersleben, 2014;Steg, 2005;Zhao & Zhao, 2015), while others are founded in a sociological perspective of studying mobilities (Watts & Urry, 2008) and the individual, localized, social, and cultural environments in which travel takes place. Although uncovering true travel motivations can be challenging due to post-hoc justifications, response inconsistencies, and blurred lines (Mann & Abraham, 2006), these kinds of questions appear to be a useful tool for examining hedonic and eudaimonic motivations related to the PUT concept.…”

Section: Noninstrumental Reasons For Travelingmentioning

confidence: 99%

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Exploring the positive utility of travel and mode choice

Singleton

2020

Mapping the Travel Behavior Genome

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Why do people travel? Underlying most travel behavior research is the deriveddemand paradigm of travel analysis, which assumes that travel demand is derived from the demand for spatially separated activities, traveling is a means to an end (reaching destinations), and travel time is a disutility to be minimized. In contrast, the "positive utility of travel" (PUT) concept suggests that travel may not be inherently disliked and could instead provide benefits or be motivated by desires for travel-based multitasking, positive emotions, or fulfillment. The PUT idea assembles several concepts relevant to travel behavior: utility maximization, motivation theory, multitasking, and subjective well-being. Despite these varied influences, empirical analyses of the PUT concept remain limited in both quantity and scope. There is a need for more fundamental development and classification of the PUT idea and its multifaceted nature. The wide variety and quality of ways to measure PUT attributes are further research challenges. Additionally, few studies investigate both major aspects of the PUT concept-travel activities and travel experiences-simultaneously. Finally, research is only beginning to examine empirical associations between PUT measures and travel behaviors such as mode choice. This dissertation addresses many of these gaps in conceptualizing, measuring, and modeling the PUT concept. First, a literature review strengthens the definition, classification, and empirical support for a PUT, defined as "any benefit(s) accruing to a traveler through the act of traveling." The two primary PUT categories are travel activities (travel-based multitasking) and travel experiences (travel subjective well-being), and the most useful PUT measures involve gathering self-reported assessments of these topics. Based on this ii review, an online questionnaire is designed and administered to nearly 700 commuters in the Portland, OR, region. The survey includes detailed questions about commute mode choice, activity participation, travel usefulness, positive emotions and fulfillment, and travel liking for a recent home-to-work trip. Next, these PUT measures are empirically examined using factor analyses, finding groupings of activities and common unobserved constructs of hedonic ("Distress," "Fear," "Attentiveness," "Enjoyment") and eudaimonic ("Security," "Autonomy," "Confidence", "Health") subjective well-being. Many of these factors exhibit large variations among travel modes-walking and bicycling commuters are the most satisfied and appear to value time spent exercising-and are predicted (somewhat less strongly) by other trip and traveler characteristics in ordered logit regression and structural equation models. Finally, integrated choice and latent variable models are estimated to examine relationships between measures of the PUT concept and commute mode choice. This is made possible by the unique dataset that collects PUT measures for not only the chosen mode but also modal alternatives. Measures of travel-based multitasking are signi...

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“…Following a similar theme, Barbeau et al (2010) explored how new mobile apps enhance rider experience by providing real-time information about their trips, including alerting customers when to disembark or enabling riders to signal the driver to stop. Guo et al (2015) observed 1,739 passengers and surveyed 686 to evaluate usage patterns on the bus system in Vancouver, British Columbia. Their study used a predictive model to evaluate the factors (such as crowding and waiting conditions) that affect how riders spend their time.…”

Section: Relevant Literaturementioning

confidence: 99%