Understanding time use: Daily or weekly data?

Commuting Time and Household Responsibilities: Evidence Using Propensity Score Matching

“…However, time use surveys can serve as a complement to National Travel Surveys, as shown by Kitamura and Fuji (), who contend that time‐use surveys should be used in order to continue developing transportation planning methodologies. The use of time‐use surveys in transportation research has become a common practice, as shown by Jara‐Díaz and Rosales‐Salas (). Furthermore, time‐use surveys are important in analyzing the relationship between commuting time and time devoted to noncommuting activities, which includes housework, childcare, and leisure.…”

Time use, mobility and expenditure: an innovative survey design for understanding individuals’ trade-off processes

“…The three survey traditions described above were combined in order to achieve the goal of collecting data about travel activities, non-travel activities and consumer expenditures from the same individuals for a 1-week period. One week seems to be a good compromise between response burden and accurate representation of the individuals’ long-term equilibrium, because intra-personal variation and routines that follow multi-day cycles can be observed for most activity types and expenditures (Jara-Diaz and Rosales-Salas 2015; Minnen et al 2015; Senbil and Kitamura 2009; Zerubavel 1985). The challenge was to merge the three survey concepts in a way that keeps the response burden at an acceptable level and at the same time delivers all required information in high quality.…”

“…Chalasani and Axhausen 2004), but information about non-travel-activities can only be roughly inferred from ‘trip purposes’ and no information about budget assignment is included. A possibility to retrieve all required information is the matching of data from independent time use and expenditure surveys (Jara-Diaz and Rosales-Salas 2015; Konduri et al 2011), but this procedure yields only probabilistic rather than direct relationships between time and budget assignment. Castro et al (2012) mentioned that the merits and appropriateness of such a synthetic data generation are debatable and further efforts on obtaining combined data on time-use and expenditure are desirable.…”

“…The goal of this study is to develop a survey design that meets all requirements formulated above and at the same time ensures acceptable response burden and high data quality. Such a survey procedure should have an observation period of at least 1 week, since this period captures the rhythms of most activity types sufficiently and is a suitable compromise between response burden and data requirements (Jara-Diaz and Rosales-Salas 2015; Minnen et al 2015; Senbil and Kitamura 2009; Zerubavel 1985). A combined data collection approach is meant to take advantage of three currently separate survey techniques: travel surveys including information about the characteristics and determinants of travel activities such as trip purpose, start and end time, duration, cost, transport modes, location of origin and destination; time use surveys giving complete information about travel and non-travel activities throughout the day including the types of main and parallel activities, location, start and end time of each activity episode; consumer expenditure surveys dealing with goods consumption and budget assignment in the short and long run.…”

Modelling commuting time in the US: Bootstrapping techniques to avoid overfitting

“…For instance, commuting can be considered in terms of time or of distance, but it is important to know how it is measured and reported (e.g., diaries, stylized questions, aggregated flows). The evidence suggests that commuting times are, in general, less biased than commuting distances (Small & Song, ), and that surveys based on diaries may represent a more accurate source of information than stylized question surveys (Gimenez‐Nadal & Molina, ; Jara‐Díaz, Bhat, & Tudela, ; Jara‐Díaz & Rosales‐Salas, ; Kitamura, Fujii, & Pas, ). Also, commuting times depend on the type of commute (active commuting, commuting by public transport, or commuting by private vehicle), and also on exogenous and stochastic factors (e.g., traffic congestion).…”