A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Carer-employees’ travel behaviour: Assisted-transport in time and space
Abstract Assisted-transport demand is a daily caregiving task that affects carer-employee’s activity-travel behaviour; however, little is known about such behaviour and the types of constraints that impact carer-employee health. Combining the principles of Hägerstrand’s time geography and Mckie et al.’s caringscape terrain, this research develops a mixed-methods framework to classify the travel behaviour of carer-employees based on their travel experience and the space-time fixity of their weekly schedules. The mixed-methods framework consists of sentiment analysis and k-means clustering, both which are used to analyze 25 randomly selected participants within the Greater Toronto-Hamilton Area (GTAH). Participants were asked to reflect on their recorded one-week trips in a trip summary questionnaire. Sentiment analysis was used to thematically describe carer-employees’ travel behavior, whereas, k-means clustering generated travel behaviour profiles. “Time”, “pressure”, “parents”, “run”, and “long” were several thematic keywords describing the carer-employees’ travel behaviour. K-means clustering identified three relative types of carer-employees’ travel behaviours: 1) flexible, 2) between flexible and fixed, and; 3) fixed. These results provide critical information for the establishment of custom transport programs, such as maximum monthly telecommuting allotment; such programs are useful for employers to use in order to alleviate assisted-transport demand on their employees.
Carer-employees’ travel behaviour: Assisted-transport in time and space
Abstract Assisted-transport demand is a daily caregiving task that affects carer-employee’s activity-travel behaviour; however, little is known about such behaviour and the types of constraints that impact carer-employee health. Combining the principles of Hägerstrand’s time geography and Mckie et al.’s caringscape terrain, this research develops a mixed-methods framework to classify the travel behaviour of carer-employees based on their travel experience and the space-time fixity of their weekly schedules. The mixed-methods framework consists of sentiment analysis and k-means clustering, both which are used to analyze 25 randomly selected participants within the Greater Toronto-Hamilton Area (GTAH). Participants were asked to reflect on their recorded one-week trips in a trip summary questionnaire. Sentiment analysis was used to thematically describe carer-employees’ travel behavior, whereas, k-means clustering generated travel behaviour profiles. “Time”, “pressure”, “parents”, “run”, and “long” were several thematic keywords describing the carer-employees’ travel behaviour. K-means clustering identified three relative types of carer-employees’ travel behaviours: 1) flexible, 2) between flexible and fixed, and; 3) fixed. These results provide critical information for the establishment of custom transport programs, such as maximum monthly telecommuting allotment; such programs are useful for employers to use in order to alleviate assisted-transport demand on their employees.
Carer-employees’ travel behaviour: Assisted-transport in time and space
Dardas, Anastassios Z. (author) / Williams, Allison (author) / Scott, Darren (author)
2019-10-02
Article (Journal)
Electronic Resource
English
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