“…We consider several socio-demographic and employment characteristics included in the UKTUS and the ATUS to build the profile of carpoolers. Specifically, we include age, gender, native status, the highest level of formal education achieved (primary education, 4 Time use surveys gather information on daily activities and travel undertaken by individuals and households, and prior literature has relied upon this type of data to analyze commuting (Gimenez-Nadal and Molina, 2016, Gimenez-Nadal, Velilla, 2018a, 2018b) and travel behaviors (Kitamura et al, 1997, Axhausen et al, 2002Gerike, Gehlert and Leisch, 2015;Rosales-Salas and Jara-Díaz, 2017;Harms, Gershuny and Olaru, 2018;Aschauer et al, 2019). Gerike, Gehlert and Leisch (2015) compare travel behavior and activity participation using the German National Travel Survey (NTS) and Time Use Survey (TUS), finding that the number of trips per person is higher in the TUS when changes in location without a trip are included.…”
Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.
“…We consider several socio-demographic and employment characteristics included in the UKTUS and the ATUS to build the profile of carpoolers. Specifically, we include age, gender, native status, the highest level of formal education achieved (primary education, 4 Time use surveys gather information on daily activities and travel undertaken by individuals and households, and prior literature has relied upon this type of data to analyze commuting (Gimenez-Nadal and Molina, 2016, Gimenez-Nadal, Velilla, 2018a, 2018b) and travel behaviors (Kitamura et al, 1997, Axhausen et al, 2002Gerike, Gehlert and Leisch, 2015;Rosales-Salas and Jara-Díaz, 2017;Harms, Gershuny and Olaru, 2018;Aschauer et al, 2019). Gerike, Gehlert and Leisch (2015) compare travel behavior and activity participation using the German National Travel Survey (NTS) and Time Use Survey (TUS), finding that the number of trips per person is higher in the TUS when changes in location without a trip are included.…”
Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.
“…In the past decades, plenty of individual-based time-use models have been pushed out based on various modelling frameworks for multiple discrete-continuous choices [ 14 – 20 ]. For more information, please refer to a review of time-use modelling [ 21 ]. Existing research of multiple discrete-continuous choices for individual time-use modeling can be classified into two groups: multivariate discrete-continuous frameworks (e.g., [ 19 , 22 – 26 ] and Karush-Kuhn-Tucker (KKT) demand systems (e.g., [ 22 , 27 – 31 ]).…”
Household time-use patterns are expected to reflect each household member’s daily activity participation and duration with intra-household interactions constrained by multiple budgets. Among various activities, the allocated activity derived from undertaking a household task is studied relatively less in the literature. Who will take an allocated activity is a discrete choice problem of household task assignment, and once a household member is assigned with one household task, other members will have more time to do other activities. To better understand household time-use patterns affected by household task assignment, this paper proposed a joint household-level multiple discrete-continuous extreme value-multinomial logit (MDCEV-MNL) model with multiple constraints. The Karush-Kuhn-Tucker (KKT) method combined with the simulation-based maximum likelihood estimation method is proposed to estimate the proposed model. Based on the household activity-travel data from Beijing of China, the proposed model is customized to explore elderly couples’ time-use patterns with intra-household interactions affected by household task assignment. Following the findings, policy implications are suggested to build an age-friendly society.
“…This section discusses the use of the duration of a willingly chosen activity as a measure of consumer utility, an approach hardly novel in social sciences even as it remains unexplored in marketing academia. For instance, researchers in time use and transportation science have long utilized the choice to engage in an activity and the duration of this chosen activity as the basis to assess individual utility, mostly within choice modelling frameworks (Jara‐Díaz & Rosales‐Salas, 2017). Bittman and Ironmonger (2011) neatly summarize the reason‐why:Time provides a fuller measure of well‐being than money because it allows us to examine simultaneously all human activity, including not just productivity in the market economy, but (1) the usually invisible aspects of non‐market production, (2) the social organisation of personal care and (3) the consumption of leisure.…”
Companions may enhance the enjoyment of information goods, services, and life in general, but how this enhancement varies over activities and social context remains underexplored. Furthermore, we ignore whether consumption makes company better as compared to non‐consumption. To address these questions, we implement a mixed methods approach. First, we validate a duration‐based measure of experienced utility on survey data; and, second, calibrate an econometric model of this utility measure on secondary data from the American Time Use Survey. Results show that relational proximity of companions reduces experienced utility, suggesting relational costs; whereas numerosity (cumulative number of companions by activity and day) may partly compensate for, or even reverse those costs of relating to others. Moreover, this balance of estimates of proximity and numerosity of companions is positive for non‐consumption but negative for consumption activities. Consumption emerges as a sub‐optimal locus for social interaction, with important implications for theory and practice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
