Nitrógeno

The socio-demographic characteristics of travelers vary over the three categories of work tours. For example, male travelers tend to make simple tours or work-based tours whereas female travelers tend to make complex work tours. Moreover, younger or millennial travelers mostly make work-based tours, while non-millennials tend toward simple or complex work tours. Travelers who make simple work tours have less flexibility regarding work arrival time

compared to the other two types of tour makers. A notable result is that zero-vehicle households tend toward complex work tours more than simple tours or work-based tours.

42 2.7.4.2 Activity-travel behavior

In this study, all sampled tours are defined as containing a work activity and using public transit in at least one trip segment. In most simple work tours, transit is used for both the work-bound and home-bound trips, thus, the share of transit-only tours is largest for simple tours. When travelers mix their non-work activities either before or after work, the transit-only fraction declines and travelers tend to combine transit with other travel modes, particularly private

vehicles. The share of public transit with walk is the largest for tours of pattern group 3 (complex tours with work-based sub-tour), with both the walk access/egress and the density proximate to the work place being the likely explanatory factors. When travelers make at least one non-work stop on the way to work (complex tours), they mostly do so to drop off a child or to buy a meal. When a non-work stop is made on the way to home, the activity tends to be buying goods or services. If travelers make a non-work stop during work (work-based sub-tours), they typically go out for lunch within walkable distance from their workplace.

2.7.4.3 Time-use behavior

To mark the differences and similarities in a broader time usage sense across the seven dominant tour patterns, an aggregate summary statistic of time spent on a work tour for work and non- work activity purposes and travel is computed. The summary is reported in Table 2.8 which provides information on the total time spent in and out of home, as well as for travel, in a full day. People making pattern 3a spent more time on travel in a day (travel time expenditure) than the people making other tour patterns. Moreover, where travelers make a non-work stop on their way to work (patterns 2b and 2d), they spend significantly less non-work activity time than for those patterns where the non-work activities are performed on the way home (patterns 2a and

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2c). This can be explained by the time constraints often imposed by the work activity that

follows in these patterns. As a result, these patterns mostly include short duration activities, such as pick up/drop off. Finally, with patterns 2a and 2c, people spend significantly less time at home than in other patterns. In pattern 2c with two non-work activities on the return home commute, more time is allocated to non-work than in the other patterns.

Table 2.8 Aggregate time-use statistics by identified tour types

Average Time-use Pa tte rn 1 Pa tte rn 2 a Pa tte rn 2 b Pa tte rn 2 c Pa tte rn 2 d Pa tte rn 3 a Pa tte rn 3 b

Total tour duration (home to home) 10h 14m 11h 26m 9h 32m 11h 4m 10h 40m 10h 49m 11h 28m Work duration 8h 23m 7h 58m 8h 3m 7h 29m 7h 23m 8h 5m 7h 53m Work travel duration 55m 49m 57m 1h 1m 48m 55m 45m Nonwork duration in work tour 0 1h 16m 34m 2h 3m 1h 6m 30m 1h 33m Nonwork travel duration in work tour 0 49m 31m 1h 6m 1h 19m 10m 46m Travel duration in work tour 2h 6m 2h 14m 2h 11m 2h 24m 2h 25m 2h 22m 2h 14m Travel time expenditure in a day*2 _{2h 18m 2h 21m 2h 22m 2h 28m 2h 34m 2h 38m 2h 17m}

In home activity duration in a day* 12h 53m 12h 11m 12h 36m 11h 43m 12h 41m 12h 17m 12h 9m Out home activity duration in a day* 8h 48m 9h 27m 9h 1m 9h 48m 8h 44m 9h 4m 9h 33m * marked variables are calculated in terms of people and other variables are calculated in terms of tours

It is hypothesized that the two home with work-based patterns, pattern 3a and 3b, with midday activity (e.g., lunch) during work are similar in structure to pattern 1 and 2a,

respectively, assuming that pattern 1 and 2a might have midday activities, such as lunch or e- shopping, that did not involve leaving the workplace (and effectively increasing work duration). Figure 2.19 shows these two pairs of similar patterns. To test this hypothesis, I conducted a Kruskal-Wallis test only to find that no statistically significant difference in total tour duration was found between pattern 1 and 3a or between pattern 2a and 3b.

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Figure 2.19 Two pairs of similar patterns