Descriptive statistics
To investigate the study participants’ characteristics and their transport-related walking, we initially present and discuss the descriptive statistics of the sample and the cleaned dataset. Table 1 summarises the socio-demographics of the participants. Overall, the data from 142 participants could be used after cleaning and pre-processing. As shown in Table 1, 108 (76.1%) participants were students and the rest were non-students; all of whom were employed (34 (23.9%)).
Table 1 Socio-demographics of participants (n = 142) Our sample is not representative of the general Australian population. For example, a large majority of the sample (123 participants, 86.6%) is younger than 30 years, while 19 participants (13.4%) are older than 40 yearsFootnote 2. Of the participants, however, a majority has access to a car (76.8%); thus, our sample resembles the Australian population’s car ownership rates. While the participants’ characteristics limit the generalisability of our findings to a broader population, they are common among young adults who are the main target of this study.
As some participants had not provided their home addresses, which were required for the purpose of this study, only the data for the participants who had declared their home addresses (n = 142) were used in the analysis. The final processed dataset includes 422 person-day of observations. Overall, there are 630 transport-related walking trip-legs in the data set made by participants (n = 124). Eighteen participants in our final sample had not any significant transport-related walking. Table 2 presents the descriptive statistics of our sample’s transport-related trip-legs (including those without any significant walking trip-legs).
Table 2 Descriptive statistics of transport-related walking As shown in Table 2, on average, the participants travelled 29.47 km on a single day, of which 1.2 km is transport-related walking. The average duration of transport-related walking is 12.26 min for the sample. However, the transport-related walking behaviour varies greatly between the participants. This variation is demonstrated by the range (0 — 17.72 km) and standard deviation (2.15 km) of the total length of the daily walking trip-legs.
Figure 2 shows the number and average distance of transport-related walking trip-legs at different times of a day for the whole sample. As shown in Fig. 2, the number of walking trip-legs is relatively low in the morning (before 7:00) and the evening (after 17:00). The number of walking trip-legs is relatively consistent between the two extremes, while it is slightly lower in the afternoon compared to the morning. This suggests that the participants tend to engage in a large proportion of incidental walking during normal working hours. Moreover, the lower number of walking trip-legs in the early mornings and late evenings can also be related to safety considerations and lighting. This finding suggests the need for holistic community-based policy responses that considers crime and disorder prevention and responses as well as safety interventions (e.g., effective lighting), in addition to the provision of footpaths and activity spaces. To fully understand such a potential relationship, however, it is necessary to conduct a rigorous investigation considering participants’ perceptions of safety and crime.
While fewer trips occur in the early morning (before 7:00) and late evening (after 20:00), the average length of walking trip-legs is usually longer at these times (as shown in Fig. 2). Between these two extremes, the mean walking distance is consistently around 800 m, although there is a drop at noon (around 12:00–13:00). Furthermore, the transport-related walking trip-legs are on average slightly shorter in the afternoon compared to the morning. This can be attributed to the temperature and weather conditions during afternoon, highlighting a potential need for shades to enhance walkability.
Travel purpose and walking
An exploratory investigation of the travel purposes identified by the participants reveals interesting patterns in the participants’ transport-related walking. Figure 3 shows the distribution of the share of walking distance based on trip purpose. As shown, most transport-related walking occurred between 7:00 and 19:00 (i.e., working hours). While the density of walking trip-legs for “work” is relatively evenly dispersed throughout the day, the density of walking trip-legs for “education” is significantly larger in the morning and the density of walking trip-legs for “shopping”, “home”, “health/wellbeing” and “accompanying someone else” is much larger in the afternoon, compared to other times throughout the day. The density of walking trip-legs for “eat/drink” and “changing mode” is greatest between 9:00 and 16:00, with its peak occurring around noon (i.e., lunch time) for the former.
In summary, morning trips are often associated with obligatory activities (e.g., education and work), while afternoon trips are usually associated with third places and non-obligatory activities (e.g., shopping, health and wellbeing, and accompanying others — social). Moreover, there is a higher likelihood of walking longer distances in the morning as a part of a trip-chain, given the larger density of walking for changing mode between 8:00 and 12:00.
Walking and activity nodes
Figure 4 delineates walking trips between different activity nodes at different times of the day (i.e., 7:00–8:00, 9:00–10:00, 12:00–13:00, 15:00–16:00 and 18:00–19:00) for the whole sample. The nodes and paths in this figure illustrate activity nodes and walking trips between them, respectively. The size of each activity node indicates the total number of transport-related walking trips that originated from that activity node (i.e., the larger each node is, the more walking trips have originated from that node). The width of each path represents the number of walking trips, while the path labels show the mean walking distance between the respective origin and destination activity nodes.
Figure 4 demonstrates that between 7:00 and 8:00 in the morning, most transport-related walking trips originated from either home or education nodes. This is the time that most participants were either leaving their home or walking from one building (on-campus college) to another to attend their classes at the university. The three largest mean walking distances during this period correspond to home–education (1342 m), shopping–shopping (1771 m), and eat/drink–education trips (1267 m). This indicates a high likelihood of long walking trips between early morning eating/drinking or home and the university for our study participants.
In the 9:00–10:00 time period, most frequently, walking trips continue to originate from the home and education nodes. Shops are also a frequently occurring origin node of walking trips during this time period. Notably, the number of walking trips originating from the education node is relatively high when compared to home and shops between 9:00 and 10:00 in the morning. This can be attributed to walking trips between buildings on the university campus. A further indication of intra-campus travel is the high number of circular trips occurring at the education node during this time period. Indeed, these trips represent the most frequent type of walking trips during this time period. Home–education and shopping–education trips are also frequent between 9:00 and 10:00 in our sample. The largest mean walking distances were associated with trips between education–eat/drink (1689 m); shopping–education (1352 m) and health–eat/drink (2028 m), suggesting that compared to intra-campus trips, those involving non-educational and potentially off-campus activities also require more walking throughout morning hours.
Patterns in transport-related walking trips during the midday time period (12:00–13:00) are similar to those displayed in the morning hours with a few notable differences. First, the workplace, along with home and education, generates the greatest number of walking trips during this period. As in the morning hours, education–education and home–education trips constitute the majority of walking trips, however, return trips between the education node and home (education–home trips) also start to become more frequent during the midday period. Walking trips between home and the educational node and those between the educational node and eating/drinking venues (off-campus) tend to be longer than those contained within the educational node during this time period.
The largest shift in patterns of transport-related walking trips was evident in the afternoon between 15:00 and 16:00. Most frequently, during this time period, transport-related walking trips are between education and home signifying the end of the study day. 15:00 is the end of school time in Australia — symbolically recognised as the end of students’ day. This may influence routine activities of the university students as well, if they are (a) first years and perhaps still engrained with the 15:00 finish times; and/or (b) have a part-time job that requires starting for the after school busy period. Circular trips are also common during this time period. The largest number of circular trips are generated at home, education, shopping and eat/drink nodes. The longest walking trips during this period were between home and a mode change node (2000 m); an education node and a mode change node (1752 m) as well as home-based circular trips (984 m). Mode change nodes indicate points of transport mode transfer, for example, walking to train travel or walking to driving. This node becomes an interesting contributor to walking trips during this period, highlighting the importance of better understanding trip chaining as a potential opportunity for increasing transport-related walking. Chaining refers to the use of multiple modes of transportation to achieve a singular journey. For example, walking from home to a train station and then catching a train to work.
Patterns of transport-related walking during the evening period, between 18:00 and 19:00, are distinct from daytime patterns in a number of ways. As expected, home, eat/drink and shopping nodes generate the majority of walking trips during this period. Most frequently, walking trips are between home and shopping nodes or comprise circular trips based around shopping or eating and drinking activity nodes. Walking trips between work and home are less frequent during the evening, but when they do occur, they are longer (7869 m on average). Walking trips from eating and drinking nodes to shops or home (628 m and 697 m, respectively) also have high mean distances compared to other trips during this time period. Overall, walking trips are much shorter during this period, compared to all other times of the day. This may be related to darkness and feelings of safety at this time of the day.
Finally, Fig. 5 shows the ratio of circular walking trips to all walking trips at different times of the day for the whole sample. As shown, there are more circular trips early in the morning (between 5:00 and 7:00) as well as late in the evening (18:00 onward). This indicates that the participants were more likely to walk from their current location to the same location (potentially their home) or a different location with the same functionality (e.g., two different shops for shopping) during these times. An exception to this trend is a high share of circular trips around 14:00. This is potentially when people walk to purchase a coffee or lunch without spending much time for eating/drinking in the same place, and they go back to their origin node.